{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "importing Jupyter notebook from utils_common.ipynb\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import cm\n",
    "from matplotlib import colors as mcolors\n",
    "from matplotlib.colors import rgb2hex\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib.dates as mdates\n",
    "import seaborn as sns; sns.set()\n",
    "from matplotlib import rcParams\n",
    "rcParams.update({'figure.autolayout': True})\n",
    "import time\n",
    "import datetime\n",
    "from datetime import timedelta\n",
    "from itertools import groupby\n",
    "from itertools import compress\n",
    "from operator import truediv\n",
    "\n",
    "\n",
    "import import_ipynb\n",
    "from utils_common import *\n",
    "from config import *\n",
    "\n",
    "from pandas.plotting import register_matplotlib_converters\n",
    "register_matplotlib_converters()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# migration data from Baidu Qianxi\n",
    "# crawlers are in the folder ./baidu_qx\n",
    "_N2P_PATH_ = './baidu_qx/n2province_rank.csv' # scrapy crawl n2province_rank -o n2province_rank.csv\n",
    "_P2P_PATH_ = './baidu_qx/p2province_rank.csv' ###### scrapy crawl p2province_rank -o p2province_rank.csv\n",
    "# travel size index: national\n",
    "_NIndex_PATH_ = './baidu_qx/nhistory_curve.csv' # scrapy crawl nhistory_curve -o nhistory_curve.csv\n",
    "# travel size index: provincial\n",
    "_Index_PATH_ = './baidu_qx/history_curve.csv' ####### scrapy crawl history_curve -o history_curve.csv\n",
    "# internal flow: city\n",
    "_IF_PATH_ = './baidu_qx/internal_flow.csv' ####### scrapy crawl internal_flow -o internal_flow.csv\n",
    "# # Where to save the figures\n",
    "_Figure_PATH_ = './figures/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 迁徙规模指数：全国为总体迁徙规模，不区分迁入或迁出；城市级区分迁入或迁出\n",
    "# Get the travel size index: national (does not distinguish between move in and move out)\n",
    "def load_NIndex_raw():\n",
    "    raw = pd.read_csv(_NIndex_PATH_)\n",
    "    data = raw[raw.inOrout == 'move_in']\n",
    "    data = data[['date', 'value']]\n",
    "    rename_dict = {'date': 'update_date',\n",
    "                    'value': 'value',\n",
    "                  }\n",
    "    data = data.rename(columns=rename_dict)\n",
    "    data['update_date'] = pd.to_datetime(data['update_date'], format ='%Y%m%d')  \n",
    "    data['update_date'] = data['update_date'].dt.date  \n",
    "    return data\n",
    "\n",
    "# 迁徙规模指数：反映迁入或迁出人口规模，省或城市间可横向对比\n",
    "# Get the travel size index: provincial (does distinguish between move in and move out)\n",
    "def load_Index_raw():\n",
    "    raw = pd.read_csv(_Index_PATH_)\n",
    "    rename_dict = {'date': 'update_date',\n",
    "                   'inOrout': 'direction',\n",
    "                   'province_name': 'province_name',\n",
    "                    'value': 'value',\n",
    "                  }\n",
    "    data = raw.rename(columns=rename_dict)\n",
    "    data['update_date'] = pd.to_datetime(data['update_date'], format ='%Y%m%d')  \n",
    "    data['update_date'] = data['update_date'].dt.date  \n",
    "    data = add_en_location(data, tag = 'province')\n",
    "    new_col = ['update_date', 'direction', 'province_name', 'province_name_en', 'value']\n",
    "    data = data[new_col]\n",
    "    # remove Tibet\n",
    "    data = data[data['province_name_en'] != 'Tibet']\n",
    "    data = data.reset_index(drop = True)\n",
    "    return data\n",
    "\n",
    "# Get the travel size ratio: from nation to province or from province to nation\n",
    "# examples:\n",
    "# 01月01日， 全国热门迁入地（目的地）是：广东省，迁入人口数量占全国迁入人口总量的13.67%\n",
    "# 01月01日， 全国热门迁出地（出发地）是：广东省，迁出人口数量占全国迁出人口总量的14.98% \n",
    "def load_N2P_raw():\n",
    "    raw = pd.read_csv(_N2P_PATH_)\n",
    "    rename_dict = {'date': 'update_date',\n",
    "                   'inOrout': 'direction',\n",
    "                   'province_name': 'province_name',\n",
    "                   'value': 'ratio',\n",
    "                  }\n",
    "    data = raw.rename(columns=rename_dict)\n",
    "    data['update_date'] = pd.to_datetime(data['update_date'], format ='%Y%m%d')  \n",
    "    data['update_date'] = data['update_date'].dt.date  \n",
    "    # the ratio is a percentage\n",
    "    data['value'] = data.apply(lambda row: data_NIndex[data_NIndex.update_date == row.update_date].value.tolist()[0]*row.ratio/100, axis=1)\n",
    "    data = add_en_location(data, tag = 'province')\n",
    "    new_col = ['update_date', 'direction', 'province_name', 'province_name_en', 'value', 'ratio']\n",
    "    data = data[new_col]\n",
    "    # remove Tibet\n",
    "    data = data[data['province_name_en'] != 'Tibet']\n",
    "    data = data.reset_index(drop = True)\n",
    "    # display some basic information\n",
    "    print('Last update: ', data['update_date'].max())\n",
    "    print('Data date range: ', data['update_date'].min(), 'to', data['update_date'].max())\n",
    "    print('Number of rows in raw data: ', data.shape[0])\n",
    "    return data\n",
    "\n",
    "# Get the travel size ratio: from province to province\n",
    "# examples:\n",
    "# 01月01日，迁入北京人口主要来源地为：河北省，占北京迁入人口总量的50.40%\n",
    "# 01月01日，北京迁出人口主要目的地为：河北省，占北京迁出人口总量的46.19% \n",
    "def load_P2P_raw():\n",
    "    raw = pd.read_csv(_P2P_PATH_)\n",
    "    rename_dict = {'date': 'update_date',\n",
    "                   'inOrout': 'direction',\n",
    "                   'inOrout_province_name': 'province_name_io',\n",
    "                   'province_name': 'province_name',\n",
    "                   'value': 'ratio'\n",
    "                  }\n",
    "    data = raw.rename(columns=rename_dict)\n",
    "    data['update_date'] = pd.to_datetime(data['update_date'], format ='%Y%m%d')  \n",
    "    data['update_date'] = data['update_date'].dt.date\n",
    "    # remove Tibet\n",
    "    data = data[data['province_name'] != '西藏自治区']\n",
    "    data = data[data['province_name_io'] != '西藏自治区']\n",
    "    data = data.reset_index(drop = True)\n",
    "    # there are two methods to calculate the travel size value:\n",
    "    # 1. using national travel size index and n2p travel size ratio\n",
    "    # 2. using provincial travel size index and p2p travel size ratio\n",
    "    # method 1 has severe leakage problem (which has been commented below)\n",
    "    # method 2 is more preferred\n",
    "    #data['nvalue'] = data.apply(lambda row: data_N2P[(data_N2P.update_date == row.update_date) & (data_N2P.direction == row.direction) & (data_N2P.province_name == row.province_name)].value.tolist()[0]*row.ratio/100, axis=1)\n",
    "    data['value'] = data.apply(lambda row: data_Index[(data_Index.update_date == row.update_date) & (data_Index.direction == row.direction) & (data_Index.province_name == row.province_name)].value.tolist()[0]*row.ratio/100, axis=1)\n",
    "    data = add_en_location(data, tag = 'province')\n",
    "    new_col = ['update_date', 'direction', 'province_name_io', 'province_name', 'province_name_en', 'value', 'nvalue', 'ratio']\n",
    "    new_col = ['update_date', 'direction', 'province_name_io', 'province_name', 'province_name_en', 'value', 'ratio']\n",
    "    data = data[new_col]\n",
    "    \n",
    "    print('Last update: ', data['update_date'].max())\n",
    "    print('Data date range: ', data['update_date'].min(), 'to', data['update_date'].max())\n",
    "    print('Number of rows in raw data: ', data.shape[0])\n",
    "    return data\n",
    "\n",
    "# Compare method 1 and method 2\n",
    "# Figure out whether the indexs are consistent and whether there exists any data leakage\n",
    "# temp = data_P2P\n",
    "def consistency_P2P(temp):\n",
    "    provinces = data_Index.province_name.drop_duplicates().tolist()\n",
    "    #nerror_list = []\n",
    "    error_list = []\n",
    "    for i in range(0, len(provinces)):\n",
    "        for j in range(i+1,len(provinces)):\n",
    "            p, q = provinces[i], provinces[j]\n",
    "            temp_in = temp[(temp.direction == 'move_in') & (temp.province_name == p) & (temp.province_name_io == q)]\n",
    "            temp_out = temp[(temp.direction == 'move_out') & (temp.province_name == q) & (temp.province_name_io == p)]\n",
    "            #nerror = list(map(truediv, temp_in.nvalue.tolist(), temp_out.nvalue.tolist()))\n",
    "            #nerror = sum(nerror)/temp_in.shape[0]\n",
    "            error = list(map(truediv, temp_in.value.tolist(), temp_out.value.tolist()))\n",
    "            error = sum(error)/temp_in.shape[0]\n",
    "            #if abs(nerror - 1) > 5e-2:\n",
    "                #print(p, q, nerror)\n",
    "            if abs(error - 1) > 20e-2:\n",
    "                print(p, q, error)\n",
    "            #nerror_list.append(nerror)\n",
    "            error_list.append(error)\n",
    "    return error_list # nerror_list, \n",
    "\n",
    "# The conclusion is:\n",
    "# Choose value instead of nvalue \n",
    "# Remove 西藏自治区 # Pay attention to 新疆维吾尔自治区 宁夏回族自治区 青海省\n",
    "\n",
    "# Create the P2P migration network\n",
    "def network_P2P(temp):\n",
    "    data = pd.DataFrame(columns=['update_date', 'source', 'target', 'value'])\n",
    "    data['update_date'] = temp.update_date\n",
    "    data['source'] = temp.apply(lambda row: row.province_name_io if row.direction == 'move_in' else row.province_name, axis=1)\n",
    "    data['target'] = temp.apply(lambda row: row.province_name if row.direction == 'move_in' else row.province_name_io, axis=1)\n",
    "    data['value'] = temp.value\n",
    "    data = data[(data.source!='西藏自治区') & (data.target!='西藏自治区')] # remove\n",
    "    # take the average (for every edge, we have two weights, one from move in and the other from move out)\n",
    "    data = data.groupby(['update_date', 'source', 'target']).mean().reset_index() \n",
    "    data = add_en_location(data, tag = 'network')\n",
    "    new_col = ['update_date', 'source', 'source_en', 'target', 'target_en', 'value']\n",
    "    data = data[new_col]\n",
    "    data.to_csv(r'./data/data_network_P2P.csv', index = False)\n",
    "    return data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the internal flow data\n",
    "def load_IF_raw():\n",
    "    # know which province a city belongs to via their zip codes\n",
    "    def from_city_to_province(row):\n",
    "        city_zipcode = [k for k,v in city_dict.items() if v == row.city_name][0]\n",
    "        province_zipcode = city_zipcode[0:2] + '0000'\n",
    "        province_name = province_dict[province_zipcode]\n",
    "        return province_name\n",
    "    raw = pd.read_csv(_IF_PATH_)\n",
    "    rename_dict = {'date': 'update_date','value': 'ratio'}\n",
    "    data = raw.rename(columns=rename_dict)\n",
    "    data['update_date'] = pd.to_datetime(data['update_date'], format ='%Y%m%d')  \n",
    "    data['update_date'] = data['update_date'].dt.date \n",
    "    data['province_name'] = data.apply(lambda row: from_city_to_province(row), axis = 1)\n",
    "    # do not include Hongkong, Macau, Taiwan and Tibet\n",
    "    data = data[~data.province_name.isin(['香港','澳门','台湾省', '西藏自治区'])]\n",
    "    data['population'] = data.apply(lambda row: city_population_dict[row.city_name], axis = 1)\n",
    "    data['value'] = data.apply(lambda row: row.ratio*row.population, axis = 1)\n",
    "    # summing up to the provincial level\n",
    "    data_province = data.groupby(['update_date', 'province_name'])[\"population\", \"value\"].apply(lambda x : x.sum()).reset_index()\n",
    "    # n stands for normalization\n",
    "    data_province['n_value'] = data_province.apply (lambda row: row.value/row.population, axis=1)\n",
    "    data_province = add_en_location(data_province, tag = 'province')\n",
    "    new_col = ['update_date', 'province_name', 'province_name_en', 'population', 'value', 'n_value']\n",
    "    data_province = data_province[new_col]\n",
    "    data_province = data_province.sort_values(by = ['update_date', 'province_name_en'])\n",
    "    data = data.sort_values(by = ['update_date'])\n",
    "    return data, data_province"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Compress warnings: everyone will be tired of warnings (pretend that they do not exist...)\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\", message=\"This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\")\n",
    "# Plot the migration index: national, provincial (move in), and provincial (move out)\n",
    "def figure_index(df, fs, subject = 'China'):\n",
    "    df = df[df['update_date'] >= datetime.date(int(2020),int(1),int(1))]\n",
    "    df = df.reset_index(drop = True)\n",
    "    if subject == 'China': # sum of provincial migration index\n",
    "        df = df.groupby('update_date')['value'].sum()\n",
    "        df = df.reset_index()\n",
    "    elif subject == 'Hubei (move in)':\n",
    "        df = df[(df['direction'] == 'move_in') & (df['province_name_en'] == 'Hubei')]\n",
    "        df = df.reset_index(drop = True)\n",
    "    elif subject == 'Hubei (move out)':\n",
    "        df = df[(df['direction'] == 'move_out') & (df['province_name_en'] == 'Hubei')]\n",
    "        df = df.reset_index(drop = True)\n",
    "        \n",
    "    timespan = (max(df.update_date) - min(df.update_date)).days + 1\n",
    "    # before the quarantine\n",
    "    T = (datetime.date(int(2020),int(1),int(21)) - min(df.update_date)).days + 1\n",
    "    # during the quarantine\n",
    "    TT = (datetime.date(int(2020),int(1),int(31)) - min(df.update_date)).days + 1\n",
    "    TTT = (datetime.date(int(2020),int(2),int(21)) - min(df.update_date)).days + 1\n",
    "    \n",
    "    first_list = [True]*T + [False]*(timespan - T)\n",
    "    second_list = [False]*TT + [True]*(TTT - TT) + [False]*(timespan - TTT)\n",
    "    first_mean = np.mean(np.multiply(df.value.tolist(), first_list))*timespan/T\n",
    "    second_mean = np.mean(np.multiply(df.value.tolist(), second_list))*timespan/(TTT - TT)\n",
    "    first_index = [first_mean]*timespan\n",
    "    second_index = [second_mean]*timespan\n",
    "    \n",
    "    fig = plt.figure(figsize = (12, 5))\n",
    "    ax = plt.subplot(111)\n",
    "    sns.set_style('whitegrid')\n",
    "    palette = plt.get_cmap('bone_r')\n",
    "    y_min, y_max = np.round(min(df.value), 1)*0.95, np.round(max(df.value), 1)*1.05\n",
    "    ax.scatter(df['update_date'], df['value'],marker = 'o', \n",
    "               color = [rgb2hex(palette(temp/y_max + 0.15)) for temp in df['value'].tolist()],\n",
    "               label = None)\n",
    "    ax.plot(df['update_date'], df['value'], linewidth = 2, color = palette(0.5), label = None)\n",
    "    ax.set_xlim(min(df.update_date), max(df.update_date))\n",
    "    ax.plot(list(compress(df['update_date'], first_list)), list(compress(first_index, first_list)), \n",
    "            linewidth = 2, color = palette(first_mean/y_max + 0.05), label = 'average plateau')\n",
    "    ax.plot(list(compress(df['update_date'], second_list)), list(compress(second_index, second_list)), \n",
    "            linewidth = 2, color = palette(second_mean/y_max + 0.05), label = 'lockdown plateau')\n",
    "    \n",
    "    ax.set_xlim(min(df.update_date), max(df.update_date))\n",
    "    ax.xaxis.set_major_locator(mdates.WeekdayLocator())\n",
    "    ax.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d'))\n",
    "    \n",
    "    # matplotlib.patch.Patch properties\n",
    "    props_first = dict(boxstyle = 'round', facecolor = palette(first_mean/y_max + 0.05), alpha = 0.5)\n",
    "    props_second = dict(boxstyle = 'round', facecolor = palette(second_mean/y_max + 0.05), alpha = 0.5)\n",
    "    \n",
    "    if y_min <= 0.5:\n",
    "        ax.set_ylim(-0.5, y_max)\n",
    "    else:\n",
    "        ax.set_ylim(y_min, y_max)\n",
    "    \n",
    "    shift = 0.3\n",
    "    \n",
    "    # place two text boxes\n",
    "    ax.text(0/timespan + 0.03, (first_mean - y_min)/(y_max - y_min) - shift,\n",
    "            'average plateau: ' + str(round(first_mean, 4)), \n",
    "            transform = ax.transAxes, fontsize = fs,\n",
    "            verticalalignment = 'center', bbox=props_first)\n",
    "    ax.text(TT/timespan + 0.03, (second_mean - y_min)/(y_max - y_min) + shift,  # - 0.25, - 0.1\n",
    "            'average plateau: ' + str(round(second_mean, 4)), \n",
    "            transform = ax.transAxes, fontsize = fs,\n",
    "            verticalalignment = 'center', bbox=props_second)\n",
    "    if subject == 'China':\n",
    "        ax.set_title(subject + ': p2p migration (' + str(round(second_mean/first_mean*100, 2)) + '%)', fontsize = fs + 2) \n",
    "    else:\n",
    "        ax.set_title(subject.split(\"(\")[0] + ': p2p migration ' + '(' + subject.split(\"(\")[1] + ' (' + str(round(second_mean/first_mean*100, 2)) + '%)', fontsize = fs + 2) \n",
    "    ax.set_xlabel('Date', fontsize = fs)\n",
    "    ax.set_ylabel('Index', fontsize = fs)\n",
    "    ax.tick_params(axis = 'both', which = 'major', labelsize = fs - 2)\n",
    "    ax.tick_params(axis = 'both', which = 'minor', labelsize = fs - 2)\n",
    "    subject = subject.replace(\"(\",\"\")\n",
    "    subject = subject.replace(\")\",\"\")\n",
    "    fig.savefig(_Figure_PATH_ + subject.replace(\" \", \"_\") + '_MI.png', dpi = 400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "# From the above conclusion: method 1 🌝 method 2 🌚\n",
    "# Get the travel size index: national\n",
    "#data_NIndex = load_NIndex_raw() \n",
    "#list_0 = data_NIndex.value.tolist()\n",
    "# Get the travel size index: provincial\n",
    "data_Index = load_Index_raw()\n",
    "# Verify that there is hardly any data leakage\n",
    "list_1 = data_Index[(data_Index.direction == 'move_in')].groupby('update_date').agg('sum').value.tolist()\n",
    "list_2 = data_Index[(data_Index.direction == 'move_out')].groupby('update_date').agg('sum').value.tolist()\n",
    "#list(map(truediv, list_0, list_1)) # agree? no\n",
    "#list(map(truediv, list_1, list_2)) # agree? yes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "update_date\n",
       "2020-01-01    191.841923\n",
       "2020-01-02    222.158732\n",
       "2020-01-03    314.644856\n",
       "2020-01-04    348.507198\n",
       "2020-01-05    329.736096\n",
       "2020-01-06    326.210814\n",
       "2020-01-07    340.276658\n",
       "2020-01-08    383.182553\n",
       "2020-01-09    440.387701\n",
       "2020-01-10    361.471054\n",
       "2020-01-11    388.286752\n",
       "2020-01-12    374.917248\n",
       "2020-01-13    382.720594\n",
       "2020-01-14    386.601044\n",
       "2020-01-15    417.341322\n",
       "2020-01-16    439.764228\n",
       "2020-01-17    474.146168\n",
       "2020-01-18    505.782824\n",
       "2020-01-19    514.142964\n",
       "2020-01-20    531.408244\n",
       "2020-01-21    593.333327\n",
       "2020-01-22    502.856068\n",
       "2020-01-23    444.474119\n",
       "2020-01-24    351.856807\n",
       "2020-01-25    189.722768\n",
       "2020-01-26    188.993153\n",
       "2020-01-27    194.663153\n",
       "2020-01-28    178.303453\n",
       "2020-01-29    157.273164\n",
       "2020-01-30    149.771592\n",
       "                 ...    \n",
       "2020-02-15     54.947095\n",
       "2020-02-16     58.914767\n",
       "2020-02-17     68.136941\n",
       "2020-02-18     79.335580\n",
       "2020-02-19     90.454288\n",
       "2020-02-20     99.943567\n",
       "2020-02-21    107.508967\n",
       "2020-02-22    124.854664\n",
       "2020-02-23    136.482343\n",
       "2020-02-24    140.105149\n",
       "2020-02-25    155.201249\n",
       "2020-02-26    157.824418\n",
       "2020-02-27    151.713648\n",
       "2020-02-28    150.029658\n",
       "2020-02-29    164.368440\n",
       "2020-03-01    156.094031\n",
       "2020-03-02    175.105444\n",
       "2020-03-03    160.563028\n",
       "2020-03-04    151.994135\n",
       "2020-03-05    151.241353\n",
       "2020-03-06    158.398448\n",
       "2020-03-07    153.727146\n",
       "2020-03-08    141.050192\n",
       "2020-03-09    154.120223\n",
       "2020-03-10    157.004017\n",
       "2020-03-11    149.410332\n",
       "2020-03-12    155.507429\n",
       "2020-03-13    152.171071\n",
       "2020-03-14    155.312608\n",
       "2020-03-15    152.433155\n",
       "Name: value, Length: 75, dtype: float64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_slice = data_Index[data_Index['update_date'] >= datetime.date(int(2020),int(1),int(1))]\n",
    "data_slice.groupby('update_date')['value'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>direction</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>value</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>4573</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>2.561285</td>\n",
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       "    <tr>\n",
       "      <th>4574</th>\n",
       "      <td>2020-01-02</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>3.126535</td>\n",
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       "    <tr>\n",
       "      <th>4575</th>\n",
       "      <td>2020-01-03</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.256258</td>\n",
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       "    <tr>\n",
       "      <th>4576</th>\n",
       "      <td>2020-01-04</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.882032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4577</th>\n",
       "      <td>2020-01-05</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.583336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4578</th>\n",
       "      <td>2020-01-06</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.674445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4579</th>\n",
       "      <td>2020-01-07</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>5.107439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4580</th>\n",
       "      <td>2020-01-08</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>5.770051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4581</th>\n",
       "      <td>2020-01-09</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>6.315019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4582</th>\n",
       "      <td>2020-01-10</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>5.300122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4583</th>\n",
       "      <td>2020-01-11</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>5.163296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4584</th>\n",
       "      <td>2020-01-12</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.688831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4585</th>\n",
       "      <td>2020-01-13</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.685494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4586</th>\n",
       "      <td>2020-01-14</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.604364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4587</th>\n",
       "      <td>2020-01-15</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.855237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4588</th>\n",
       "      <td>2020-01-16</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.851414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4589</th>\n",
       "      <td>2020-01-17</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>5.103518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4590</th>\n",
       "      <td>2020-01-18</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>5.420714</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4591</th>\n",
       "      <td>2020-01-19</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>5.487296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4592</th>\n",
       "      <td>2020-01-20</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>6.032524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4593</th>\n",
       "      <td>2020-01-21</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>7.211722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4594</th>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>6.795349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4595</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>6.214741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4596</th>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.589881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4597</th>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>4.387122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4598</th>\n",
       "      <td>2020-01-26</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>5.197187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4599</th>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>1.980158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4600</th>\n",
       "      <td>2020-01-28</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.870134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4601</th>\n",
       "      <td>2020-01-29</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.543121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4602</th>\n",
       "      <td>2020-01-30</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.404806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4618</th>\n",
       "      <td>2020-02-15</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.413716</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4619</th>\n",
       "      <td>2020-02-16</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.360871</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4620</th>\n",
       "      <td>2020-02-17</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.361422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4621</th>\n",
       "      <td>2020-02-18</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.378238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4622</th>\n",
       "      <td>2020-02-19</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.402311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4623</th>\n",
       "      <td>2020-02-20</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.424732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4624</th>\n",
       "      <td>2020-02-21</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.472003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4625</th>\n",
       "      <td>2020-02-22</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.580025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4626</th>\n",
       "      <td>2020-02-23</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.724367</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4627</th>\n",
       "      <td>2020-02-24</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.817873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4628</th>\n",
       "      <td>2020-02-25</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.938725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4629</th>\n",
       "      <td>2020-02-26</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.903895</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4630</th>\n",
       "      <td>2020-02-27</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.454702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4631</th>\n",
       "      <td>2020-02-28</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.320760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4632</th>\n",
       "      <td>2020-02-29</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.295229</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4633</th>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.294548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4634</th>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.289721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4635</th>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.273132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4636</th>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.275270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4637</th>\n",
       "      <td>2020-03-05</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.285379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4638</th>\n",
       "      <td>2020-03-06</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.300510</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4639</th>\n",
       "      <td>2020-03-07</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.329054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4640</th>\n",
       "      <td>2020-03-08</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.339131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4641</th>\n",
       "      <td>2020-03-09</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.336636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4642</th>\n",
       "      <td>2020-03-10</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.345287</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4643</th>\n",
       "      <td>2020-03-11</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.350568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4644</th>\n",
       "      <td>2020-03-12</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.339682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4645</th>\n",
       "      <td>2020-03-13</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.418705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4646</th>\n",
       "      <td>2020-03-14</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.726862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4647</th>\n",
       "      <td>2020-03-15</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>1.258157</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>75 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     update_date direction province_name province_name_en     value\n",
       "4573  2020-01-01  move_out           湖北省            Hubei  2.561285\n",
       "4574  2020-01-02  move_out           湖北省            Hubei  3.126535\n",
       "4575  2020-01-03  move_out           湖北省            Hubei  4.256258\n",
       "4576  2020-01-04  move_out           湖北省            Hubei  4.882032\n",
       "4577  2020-01-05  move_out           湖北省            Hubei  4.583336\n",
       "4578  2020-01-06  move_out           湖北省            Hubei  4.674445\n",
       "4579  2020-01-07  move_out           湖北省            Hubei  5.107439\n",
       "4580  2020-01-08  move_out           湖北省            Hubei  5.770051\n",
       "4581  2020-01-09  move_out           湖北省            Hubei  6.315019\n",
       "4582  2020-01-10  move_out           湖北省            Hubei  5.300122\n",
       "4583  2020-01-11  move_out           湖北省            Hubei  5.163296\n",
       "4584  2020-01-12  move_out           湖北省            Hubei  4.688831\n",
       "4585  2020-01-13  move_out           湖北省            Hubei  4.685494\n",
       "4586  2020-01-14  move_out           湖北省            Hubei  4.604364\n",
       "4587  2020-01-15  move_out           湖北省            Hubei  4.855237\n",
       "4588  2020-01-16  move_out           湖北省            Hubei  4.851414\n",
       "4589  2020-01-17  move_out           湖北省            Hubei  5.103518\n",
       "4590  2020-01-18  move_out           湖北省            Hubei  5.420714\n",
       "4591  2020-01-19  move_out           湖北省            Hubei  5.487296\n",
       "4592  2020-01-20  move_out           湖北省            Hubei  6.032524\n",
       "4593  2020-01-21  move_out           湖北省            Hubei  7.211722\n",
       "4594  2020-01-22  move_out           湖北省            Hubei  6.795349\n",
       "4595  2020-01-23  move_out           湖北省            Hubei  6.214741\n",
       "4596  2020-01-24  move_out           湖北省            Hubei  4.589881\n",
       "4597  2020-01-25  move_out           湖北省            Hubei  4.387122\n",
       "4598  2020-01-26  move_out           湖北省            Hubei  5.197187\n",
       "4599  2020-01-27  move_out           湖北省            Hubei  1.980158\n",
       "4600  2020-01-28  move_out           湖北省            Hubei  0.870134\n",
       "4601  2020-01-29  move_out           湖北省            Hubei  0.543121\n",
       "4602  2020-01-30  move_out           湖北省            Hubei  0.404806\n",
       "...          ...       ...           ...              ...       ...\n",
       "4618  2020-02-15  move_out           湖北省            Hubei  0.413716\n",
       "4619  2020-02-16  move_out           湖北省            Hubei  0.360871\n",
       "4620  2020-02-17  move_out           湖北省            Hubei  0.361422\n",
       "4621  2020-02-18  move_out           湖北省            Hubei  0.378238\n",
       "4622  2020-02-19  move_out           湖北省            Hubei  0.402311\n",
       "4623  2020-02-20  move_out           湖北省            Hubei  0.424732\n",
       "4624  2020-02-21  move_out           湖北省            Hubei  0.472003\n",
       "4625  2020-02-22  move_out           湖北省            Hubei  0.580025\n",
       "4626  2020-02-23  move_out           湖北省            Hubei  0.724367\n",
       "4627  2020-02-24  move_out           湖北省            Hubei  0.817873\n",
       "4628  2020-02-25  move_out           湖北省            Hubei  0.938725\n",
       "4629  2020-02-26  move_out           湖北省            Hubei  0.903895\n",
       "4630  2020-02-27  move_out           湖北省            Hubei  0.454702\n",
       "4631  2020-02-28  move_out           湖北省            Hubei  0.320760\n",
       "4632  2020-02-29  move_out           湖北省            Hubei  0.295229\n",
       "4633  2020-03-01  move_out           湖北省            Hubei  0.294548\n",
       "4634  2020-03-02  move_out           湖北省            Hubei  0.289721\n",
       "4635  2020-03-03  move_out           湖北省            Hubei  0.273132\n",
       "4636  2020-03-04  move_out           湖北省            Hubei  0.275270\n",
       "4637  2020-03-05  move_out           湖北省            Hubei  0.285379\n",
       "4638  2020-03-06  move_out           湖北省            Hubei  0.300510\n",
       "4639  2020-03-07  move_out           湖北省            Hubei  0.329054\n",
       "4640  2020-03-08  move_out           湖北省            Hubei  0.339131\n",
       "4641  2020-03-09  move_out           湖北省            Hubei  0.336636\n",
       "4642  2020-03-10  move_out           湖北省            Hubei  0.345287\n",
       "4643  2020-03-11  move_out           湖北省            Hubei  0.350568\n",
       "4644  2020-03-12  move_out           湖北省            Hubei  0.339682\n",
       "4645  2020-03-13  move_out           湖北省            Hubei  0.418705\n",
       "4646  2020-03-14  move_out           湖北省            Hubei  0.726862\n",
       "4647  2020-03-15  move_out           湖北省            Hubei  1.258157\n",
       "\n",
       "[75 rows x 5 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_slice = data_Index[data_Index['province_name_en'] == 'Hubei']\n",
    "data_slice = data_slice[data_slice['update_date'] >= datetime.date(int(2020),int(1),int(1))]\n",
    "data_slice = data_slice[data_slice['direction'] == 'move_out']\n",
    "data_slice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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//0tBQUGZWaQTJ06Qnp5+ziINf/bpp5/i4+ND165dWb16NYcPH+b9998HYMOGDWzYsIGxY8cSFBRUpsqbs7NzmRmMp556iuzsbHx8fHjjjTfw9PS8YEJ2uUaPHs3ixYuZPHkyU6ZMobi4mFdeeQWDwVCmvPlfhYaG4urqyqJFi7BYLOTl5fHhhx9y6NAhDAYDVqsVg8GAh4cHSUlJbN68ucy+MCiZybz99ttZunQpJpOJ7t27s2PHDpYuXcqdd96Jp6fnJX+u3r17U1RUxK+//lqpgg/XXnstfn5+PPLII9x7771ERUWxYMECJkyYUKZAxt69e/Hx8SlTAOXIkSN4e3uXO14ASvaMDRw4kOeeew6DwUBhYSHPPPMMbdq0KbdfC0pm0n766Sc2bNhga+vfvz/vvvsu3t7eLFu2rFxxl+PHj5OZmck111xT4c8rImIvSrBERKqYwWDg5ZdfZsWKFURERPDNN99QUFBA8+bNmTNnDjfeeOMFf8G/XL179+axxx5j2bJlfPbZZwQGBjJ8+HDMZjPLli2joKAAR0dHFi1axKpVqzh8+PAFnzdt2jQ2bNjAkiVLaN26NUuWLLEtlys9r2v16tWsXr26zH2tWrVi3bp1ttezZ89m4cKFpKen06tXL1577bVzHohbVRwcHFi6dCnz5s1j1qxZuLu7c9999/Huu++ec29XKXd3dxYuXMgLL7zAAw88gLe3N+Hh4bz66qtMmTKFffv20aVLFyZMmMAPP/zA/fffzwsvvFDuOTNnzsTb25tPPvmEJUuW0LhxY2bNmsXEiRMv63OFhobSsmVLNm/eXKkEy83NjSVLljB//nweeughvL29+cc//mFbpldqwoQJ3HDDDTz33HO2trS0tHJ76P7s2Wef5ZlnnmHOnDkYDAauvfZaZs6cec79Wq+++ip33XVXma/99OnTefTRR5k+fTq9e/dm6tSpZe75+eefCQwMvKyZPxGRmmKwXsp6ERERueLFx8czaNAgXn311XLV8CojIiKCxx57jC1btlTrnqu/Onz4sO0zlMrKyqJ3797MnDmTO+64o8ZiqWoRERG89tprfP/99xdcqnilGD16NOPGjWPSpEn2DkVE5KKu/J/KIiJSL509e5YHH3yQV155hW3btvHdd9/xwAMP4OrqWq70fF0zevRoXF1dy+3xuhL98ssvZGVlcfPNN9s7FBGRClGCJSIiV6Tw8HBefPFFNm7cyP3338/s2bNxc3Pjgw8+KFdEoa4xm80899xzLFy4kMLCQnuHU22sVisvvfQSTz/99CWXphcRqWlaIigiIiIiIlJFrtgiFxaLhezsbBwcHKp1M7mIiIiIiFyZrFYrhYWFuLq6VnjP6xWbYGVnZxMVFWXvMEREREREpI5r3bp1hSvfXrEJloODA1AyGOcqE1sf7N+/v9zZLFKexqniNFYVp7GqGI1TxWmsKkbjVHEaq4rTWFXMlThOBQUFREVF2XKLirhiE6zSZYGOjo44OTnZORr7qc+fvTI0ThWnsao4jVXFaJwqTmNVMRqnitNYVZzGqmKu1HGqzJYjVREUERERERGpIkqwREREREREqogSLBERERERkSqiBEtERERERKSKKMESERERERGpIkqwREREREREqkiNJliHDx/m9ttvZ+zYsYwbN479+/cD8OabbzJs2DCGDBnCwoULsVqtAKSnp3PPPfcwYsQIRo4cye7du2syXBERERERkUqpsQQrNzeXu+++m3vuuYfVq1fz4IMPMmPGDDZu3Mj69euJiIhg3bp1bNu2jfXr1wMwb948wsPD+fLLL3nxxReZOnUqubm5NRWyiIiIiIhIpdRYgrV582aCg4Pp378/AIMGDWLBggVs2LCBkSNH4uLigpOTE+PGjWPt2rUUFRXx448/ctNNNwHQtm1bmjVrxqZNm2oqZBH5XWZmJmvWrOGXX36hoKDA3uGIiIiI1FrmmuooOjqahg0b8vjjj3Po0CE8PDyYOXMmiYmJ9O7d23ZdYGAgycnJnD59GovFgo+Pj+29gIAAkpKSKtVv6TLE+mrXrl32DqFO0Did37p163j22Wcxm0t+XDz++OMsWLCALl262Dmy2k/fVxWjcao4jVXFaJwqTmNVcRqritE41WCCVVRUxMaNG1m+fDmdO3fm22+/5b777iM0NBSDwWC7zmq1YjQasVgsZdpL3zOZTJXqt0OHDjg5OVXJZ6hrdu3axVVXXWXvMGo9jdP5HT58mOeff578/Hzy8/Nt7dOnTycxMRFXV1c7Rle76fuqYjROFaexqhiNU8VprCpOY1UxV+I45efnV3rCpsaWCPr7+9OiRQs6d+4MwODBgykuLsZoNJKSkmK7LiUlhcDAQHx9fbFarWRkZJR5LyAgoKZCFqn3li1bRmFhIQaDgUEjJtD9miG299atW2fHyERERERqpxpLsPr160d8fLwtA9yxYwcGg4GJEyeydu1acnJyKCgoICIigsGDB2M2mxkwYAArVqwA4NChQxw7doyePXvWVMgi9d6ZM2coKiqiSUhLOnTpRa++1+Hg4EhxcTFnz561d3giIiIitU6NLRFs2LAhb7zxBvPmzSM3NxdHR0cWLlxIeHg4UVFRjB8/nsLCQgYNGsTYsWMBeOKJJ5gzZw4jR47EYDDwwgsv4O7uXlMhi9R7o0aNYtmyZbRu1w0Ao9FEYONmpCadYMiQIRe5W0RERKT+qbEEC6B79+58+umn5donT57M5MmTy7X7+fmxePHimghNRM5h6NChDBo8mKAWnW1tzULDmHjbTYSEhNgxMhEREZHaqUYPGhaRusVoNDL/6Zdwcm6A1WoB4LoRo5k/f76dIxMRERGpnZRgicgF7dkfBcC1fcIBOHM2j+LiYnuGJCIiIlJrKcESkfPKLyjkQORxAPr17oKHWwMKCouIS0i5yJ0iIiIi9ZMSLBE5r/2RxygoLKJ500b4eHvg7+sBwPGYBDtHJiIiIlI7KcESkfPa/WvJ8sBuncIA8PfzBOB4zEm7xSQiIiJSmynBEpFzys7J49CRGAwGA106tgLA3+/3GazYBCwWqz3DExEREamVlGCJyDn9euAoxcUWWrcIxt3NFQA3F2c83V3Jyc0j5VS6nSMUERERqX2UYInIOe3+9TAAXTuG2doMBgOhzRoDcEzLBEVERETKUYIlIuWcyczmaHQcJpOJTu1blHkvNCQIUKELERERkXNRgiUi5ezdH4XVCm1bh+DSwLnMe6UzWMdjNYMlIiIi8ldKsESknNLlgaXVA/+sUYAvzs6OnM44y+mMzJoOTURERKRWU4IlImWcSj9DbFwSjo4OdGgTWu59o9FIaNOSZYLHtExQREREpAwlWCJSxp7fZ686tg3F0dHhnNfYlgmq0IWIiIhIGUqwRKSMCy0PLKV9WCIiIiLnpgRLRGwSk0+RmJyGSwMnwlqGnPe6po39MZtNJKWkk52TW4MRioiIiNRuSrBExGb3vpLZq87tW2E2m857ndlsJqRJIADRsdqHJSIiIlJKCZaIAGC1Wtn9WxQA3Tqff3lgqT8OHFaCJSIiIlJKCZaIAHAiPpm09DN4uLvS4vfk6UJCm/1+4LD2YYmIiIjYKMESEeCP4hZdO7bGaLz4j4bmwY0wGAzEnUwhv6CwusMTERERqROUYIkIFouFPaXLAy9QPfDPnJ2daBzoh8ViITYuqTrDExEREakzlGCJCMdiTpJ5Nhs/H0+aNgmo8H06D0tERESkLCVYImKrHti1UxgGg6HC9/1xHpYKXYiIiIiAEiyReq+oqJh9B44AFV8eWKrF74UuYuISKS62VHlsIiIiInWNEiyReu7w0VhycvNpFOBHowDfSt3r7uZKQ18vCgoKOZmYUk0RioiIiNQdZnsHICL28dtvv/Hf//6XAoMnbl4BdGzb/JKeE9qsMalpGRyLSaDp74cPi4iIiNRXmsESqYc++eQTevXqxdtvv4OjixcAT/xrBllZWZV+lu08LBW6EBEREVGCJVLf5Ofnc++995KTk0PT0DY4OjqReDKGA/v3sXjx4ko/r0XIH4UurFZrVYcrIiIiUqcowRKpZ/bs2YPBYMDdw4sefYYCEHVwD7m5uaxYsaLSz/P18cTD3ZXsnFySU09XdbgiIiIidYoSLJF6xt3dHf/Aptx81yP4NWxERnoqkb/tBMDLy6vSzzMYDFomKCIiIvI7JVgi9YjVauXUmQKGj7sTFxc3Yo5F8vG7C8jPy8HV1ZWHHnrokp4bGqLzsERERERAVQRF6o3CwiJWrPmOHXsiMRqNRB3YweYf1uHoYAKrE1OmTGHUqFGX9OzQkN9nsGI1gyUiIiL1mxIskXrgdMZZ3v5wHXEnk3F0MHPL34bSuf0Ufv75Z1JTU7n66qtp1KjRJT8/KNAPZydH0k9nknHmLF6e7lUYvYiIiEjdoQRL5ApTXFzMqVOn8Pb2xtHRkWPR8bzz0RdkZefi6+3B3beNIiiwIQD9+vWrkj6NRiPNQ4KIjIrhWMxJrurcpkqeKyIiIlLXKMESuYIsWbKUOXPmkJOTi9Fo5J4HpmExe2GxWAhr2ZQ7JgzH1aVBtfQd2qwkwToek6AES0REROotJVgiV4hVq1YzY8ZMcnJyMJnM9BsyliKjB1gsXNvnKkYOvQaTqfrq2vxxHpb2YYmIiEj9pSqCIleI+fP/TU5OLkHBoYy9+T7adgynsLCAn76JYPigntWaXAE0bRKA2WwiMTmN7Jy8au1LREREpLbSDJbIFSDjTBYefk34+73D8fTyBSDzzGnWr15O1pl0MjMz8fPzq9YYzGYzTZsEcjzmJDEnEmjfJrRa+xMRERGpjTSDJVLLJSYmcccdk/D19ScgIIipU6dx9uxZiouL+fXgUd5avoZ5Ly6lS/cBeHr5kpWZwY5fvuPT5QtJS0nE3d0dHx+fGom1xe/l2o/pwGERERGppzSDJVKL5eTk0Ldvf5KTkykqKgIgYvU6ktLzad2uK2ezcgAwmYw0DvBhyeJXORZ1AKvVCoCLiwvPPvs0RmPN/C0lJDgQgJ82bycrPZ4bbhhLgwbVU1RDREREpDZSgiVSi61c+RkZGRkUFRUREtqGzuF9aNSkGQBns3IIaOhDr/AOdO/aBjdXF/r2aMOcOf/Hvn37CA4OZu7cOYwefWmHB1dWRkYGd068nasHjye/0Mojj8zk8cf/xQ8/fEfz5s1rJAYRERERe6vRBOu5557jq6++wtPTE4DmzZuzYMEC3nzzTVatWkVxcTGjR4/moYcewmAwkJ6ezqxZs0hISMBoNPLUU0/RrVu3mgxZxK727NlLdnY2jYNDGTb2NgAKC/KJORbJoH49mD71dgwGg+367t278/XX6+0S67x5T3Ek6jBhnZPw82+Ei7s3yQknuP/+B/jmm6/sEpOIiIhITavRBGvPnj28/PLLZZKkjRs3sn79eiIiIjCZTNx99920aNGCESNGMG/ePMLDw5k8eTKRkZHcd999fPPNN1pyJPVG27Zt8fTypv914wD4bfcv7Nj8LU5Ojkx/sGxyZW+ffvoZBQUFJJ2Mwc+/EY2aNCcxPoatW7eRk5ODi4uLvUMUERERqXY1VuSioKCAgwcPsmTJEkaNGsXDDz9MQkICGzZsYOTIkbi4uODk5MS4ceNYu3YtRUVF/Pjjj9x0001AyS+azZo1Y9OmTTUVsojd3XzzTfTsex3uHl6kJMWz9aevACtBQY0YOPBae4dXRmmyFx97FIDQ1h3sGY6IiIiIXdTYDFZycjK9evVi2rRptGrViqVLl/Lggw/i6+tL7969bdcFBgaSnJzM6dOnsVgsZaqfBQQEkJSUVKl+9+/fX2WfoS7atWuXvUOoE2rrOMUnptG8VQcslmI2frMKg8HANdf0ZsaMR9izZ49dYjrfWA0Y0J+1az8nLvYouTnZ+Pj60zCwMcFB/kRGRtZwlLVDbf2+qm00ThWnsaoYjVPFaawqTmNVMRqnGkywgoODeeutt2yv7777bhYtWoS3t3eZZU5WqxWj0YjFYim3/MlqtWIymSrVb4cOHXBycrq84OuoXbt2cdVVV9k7jFqvto5Tdk4ua755D4Abrh/Ay/OnYjAYKv3/QFW60Fi98cZCDh06TGxsLMejfqN9l14LCs7CAAAgAElEQVR07tab11+eR9OmTWs4Uvurrd9XtY3GqeI0VhWjcao4jVXFaawq5kocp/z8/EpP2NTYEsFDhw6xevXqMm1Wq5WgoCBSUlJsbSkpKQQGBuLr64vVaiUjI6PMewEBATUVsohdrfz8BzKzcght1pj+V3fFbDbbNbm6GA8PD7Zu3cx77y1jQJ9wADp27Unjxo3tHJmIiIhIzamxBMtoNPL0008TFxcHwIcffkhYWBiDBg1i7dq15OTkUFBQQEREBIMHD8ZsNjNgwABWrFgBlCRox44do2fPnjUVsojd7Pktij2/RuHo6MCt44bU2DlWl8tkMnHddUN5fPYjBPr7kp2TR2RUjL3DEhEREakxNbZEsHXr1syZM4cHHniA4uJiAgMDefnllwkKCiIqKorx48dTWFjIoEGDGDt2LABPPPEEc+bMYeTIkRgMBl544QXc3d1rKmQRu8g8m83Ktd8DMGZYX/x8vewcUeUZDAa6d23L51//zI49kXRo28LeIYmIiIjUiBot0z5mzBjGjBlTrn3y5MlMnjy5XLufnx+LFy+uidBEagWr1conq78jOyePsJZNubpHR3uHdMnCu7Rh3Teb2X8omuycPFxdnO0dkoiIiEi1qxvrjkTqie17DnLg0HGcnR25+YYhteqcq8ry9HCjdYtgiouL2fPbYXuHIyIiIlIjlGCJ1BKnMzJZtW4jAONGDsDbq+4vh+3etR0AO/bUzzLtIiIiUv8owRKpBSwWKx9FfEtefgEd2obSvUtbe4dUJTq1a4GTowOxcUmknDpt73BEREREqp0SLBE7sVqtHDhwkB9//IlvN24j6tgJXF2cmTB2UJ1eGvhnjo4OdO7QCtAsloiIiNQPSrBE7CAxMZF+/YYwfPhYHp4yk7XrNwEwfswg3N1c7Rxd1eretWQ2bufeSCwWq52jEREREaleSrBE7OC22+4mKuoIubm5dAzvi9nBgRPRUaQknLB3aFWuRbMmeHu5czrjLMdi4u0djoiIiEi1UoIlUsOio2M4fDiK4uJi2nS8Cv9GTcjJzmLrxm94880l9g6vyhmNBtueMi0TFBERkSudEiyRGnb6dAYODmbc3D3pHH4NAFs3fk1Bfh5paWl2jq56hP++THDf/iPkFxTaORoRERGR6qMES6SGtW/fFqvVSo++gzE7OBB95CAJcdE4OTkybNhQe4dXLfz9vGnWtBH5BYX8dvCYvcMRERERqTZKsERqmJOTEzNmP05QcHPy8/PYteVHnJ2d8Pf3Z/Lke+wdXrX5Y5ngQTtHIiIiIlJ9lGCJ1LCc3DyST+cDYCjIpGuXjsya9QgbN36Dl5eXnaOrPl06tsZkMhF17AQZZ7LsHY6IiIhItTDbOwCR+mbdN5s5m5VD85AgHr5nKkbjlXHm1cW4ujjToW0o+/YfYee+SAb3627vkERERESqnGawRGpQdGwCv2z/DZPJyE1jBtWb5KpU6TLBnXsisVp1JpaIiIhceZRgidSQ4uJiVqz5DoCBfcNpFOBr54hqXtvWIbi5NiApJZ34hBR7hyMiIiJS5ZRgidSQH37eTWJyGn4+ngwZ0MPe4diFyWSiW+cwALbrTCwRERG5AinBEqkBp9LP8PX3WwEYP2Ygjg71d/tj9y7tANi97zBFRcV2jkZERESkainBEqlmVquVlWu/p7ComKs6tyGsZYi9Q7KrJkENCfT3JTsnl0NHYuwdjoiIiEiVUoIlUs32/BbFoSOxuDRwYuyIfvYOx+4MBgM9upUUu9AyQREREbnSKMESqUY5uXlErNsIwKjr+uLu5mLniGqHqzq3wWCAXw8c5fF/PcXXX39LcbGWC4qIiEjdpwRLpBp9/vXPZGXnENqsMT2vam/vcGqNnTt2kpKYAMAv2/YxbdpsJkyYREFBgZ0jExEREbk89XenvVTK/v0H+eKLbzAaDFw/chjt2oXZO6RaKyPjDFFRR7EaHNiyY//vZ14NrHdnXp1PQUEBU6c+iqevPw0Dg2ga2proI5Hs33+ATz9dxd//PsHeIYqIiIhcMiVYclEvvfgaS5e+Z5tdePvt93nwwbt5eMpkO0dWu1itVp555j+8t/xjnJycCO83BHdPL/r26kygf/078+p89u3bj9VqITEuhsLCAnwaBuDq7kH22UxWrfpcCZaIiIjUaVoiKBd0+PARli5dTl5eHhaLBYvFQl5eHm8sWkJ0dKy9w6tVPvn4Mz54fwX5+fkEBDfD3dOL7LOZfL/+C3uHVqs4OTlitVopLi4m+WQcAA0DggBwdna2Z2giIiIil00JllzQt9/+SGFhEQaDgX7DRtNnyPUAWIotfPvtj/YNrpZ5661l5Obm4ubhSViHrgDs276Zr7/+lpycHDtHV3t06NAOd3d3ANJSkwDwbRiIi0sDbr31JnuGJiIiInLZlGDJBZnNZoxGI/6NmuDt2xBf/0DcvbwxGo2YzVph+mcZGWdwcXXj6kHDMZnNxB0/QmpSAmAgO1sJVimj0cjbby/Cy8uT3KwzAPgGNGLcuNEMHz7EztGJiIiIXB4lWHJBI0YMwWg00rRFK1ubf2BjAIYPH2yvsGqla/r05urBI2jg4sqplCT2bd8MgI+vN35+2oP1Z+3bt2X79o3MnTMDo9GAq5s7sx6dgcGgQiAiIiJStynBkgsKDm7C4/+aQWCTpra2wMbB/PvpuQQGBtgxstrlbFY2vk1a4ermTkZaKtt++Aar1UqDBs4888z/KXE4BycnR64fMZRWocEARJ9IsHNEIiIiIpdPCZZcVPNWbTAaTbg2cABKEqwxY663c1S1R3ZOLovejuD0mSz8/bwIDfKibdtWjBw5jE8/Xc611/azd4i1WvOmJQUuomOVYImIiEjdp000clHbdx8E4G+jB/PdTzs5mZjK8dgEwlo2vcidV77cvHwWv7OKxOQ0Ahr68PC9N+Lm6mLvsOqU0GYlCdZxJVgiIiJyBdAMllxQQtIp4hJSaODsRMe2LWxJ1eGjKtGen1/A/5atJi4hBT8fTx68a5ySq0sQ0iQQo9HAycQU8gsK7R2OiIiIyGVRgiUXVDp71a1TGA4OZtq0CgHg0JH6nWAVFBax5P21RJ9IxMvTnQfv+hueHm72DqtOcnJypHFgQywWK7FxSfYOR0REROSyKMGS8youLmbn3kMA9OjWDijZL+PgYCYh6RRns7LtGV6NS0lJ5dSpdIqKinjnw3UcOR6Ph7sr/7j7b/h4e9g7vDqteYj2YYmIiMiVQXuw5Lwio2LJys4hoKEPTZuUVAx0cDDTolljDh2J5fDROMK7tLFzlNUvMjKKGTP+j/j4RAwGAz37XUsDd09cXRrw4F3jaOjrZe8Q67zQkCB+2rKX47En7R2KiIiIyGXRDJac1/bdBwDoeVW7MmXGw1qWLBOsD/uwzpzJ5I47HuT48VgKCgpp3bErDdw9KSos5N7bRxHor/OtqkLpDFZMXBIWi8XO0YiIiIhcOiVYck5Z2TnsPxSNwWDgqs5ty7zXptXvhS6OxGK1Wu0RXo1Zt+5rioqKAWjX9SqCmoZQVFjI/l1biToUZeforhyeHm74enuQn19AQtIpe4cjIiIicsmUYMk57dp3GIvFQttWIXh6uJZ5L9DfFw93VzKzckhMTrNThDUjPj6RvLw8gpo2I7h5C4qLitj9yyZOn0olKSnZ3uFdUWz7sE4k2jkSERERkUunBEvOqbR6YGlxiz8zGAz1plx7ly4d8Pb1pW3nbgAc3LuL02mpmEwmOnZse5G7pTJU6EJERESuBEqwpJz4hBROJqbi0sCJDm1Dz3nNH/uwTtRkaDVuwIA+dArvidnBgaSTcSSciMHZ2YnOndvTpUtHe4d3RQkN0YHDIiIiUvepiqCUs2NPJADdOrXBbD73t0hYy2AAjkXHU1hYhIPDlfmt9NPWvTi7umMyQnriCYKDG/O3v43izjtvKVP4Qy5fQENfGjg7kXHmLKczMvH2Uul7ERERqXuuzN+K5ZIVFZU/++pc3N1cadyoIScTUzkem2BbMngliTuZwvpvtwJwzx1jaTt/mp0jurIZjQaaN23EwagYjscmcJUSLBEREamDtERQyjgYFU12Ti6NAnwJbux/wWuv5H1YBYVFvP/pV1gsFvr26kzbVs3sHVK90LxZ6T4sFboQERGRuqnGE6xvv/2Wrl272l6/+eabDBs2jCFDhrBw4UJb2e/09HTuueceRowYwciRI9m9e3dNh1ov/bm4xcWWwLVpVbIP69CRKy/B+vzrn0lOTce/oTejrutj73DqjdCmpfuwdOCwiIiI1E01mmDFxMTw/PPP215v3LiR9evXExERwbp169i2bRvr168HYN68eYSHh/Pll1/y4osvMnXqVHJzc2sy3HrnbFYOBw/HYDQauKpzm4te37xpEA5mEwlJpziblV0DEdaMyCMxbNqyF6PRyO3jh+Po6GDvkOqN4CaBmExGEpPTyM3Lt3c4IiIiIpVWYwlWbm4uM2fOZPbs2ba2DRs2MHLkSFxcXHBycmLcuHGsXbuWoqIifvzxR2666SYA2rZtS7Nmzdi0aVNNhVsv7dp3qOTsq9bN8XB3vej1Dg5mWjRvAsDho3HVHV6NyM7J5aPPNgAwfHCviy6TlKrl6GCmSZA/VquVmDgtExQREZG6p8aKXPzf//0fEyZMICwszNaWmJhI7969ba8DAwNJTk7m9OnTWCwWfHx8bO8FBASQlJRU6X73799/eYHXcbt27arQdVarlR9/LlmG6efpVOH7XJ1LcvRftu3GUFx3Z7F27dqF1Wrlp22RZJ7Nxt/XAy9XY4XHoT6p7jFxdTYB8MvWXeRk1u2DrPX9UzEap4rTWFWMxqniNFYVp7GqGI1TDSVYH3zwAWazmRtvvJH4+Hhbu9VqLbPPx2q1YjQasVgs5fb/WK1WTCZTpfvu0KEDTk5Olx58HbZr1y6uuuqqCl0bn5BCRubPuLo4M2rEYMzmio11UJMQdv0Wzan0LLp161YnS5eXjtP23Qc5kZCGk5Mj90/6G74+nvYOrdapzPfUpXJo4MnBIyfJK7BWe1/VqSbG6kqgcao4jVXFaJwqTmNVcRqrirkSxyk/P7/SEzY1kmCtWrWKvLw8xowZQ2Fhoe3f7dq1IyUlxXZdSkoKgYGB+Pr6YrVaycjIwMvLy/ZeQEBApfueOHE2GRlnq+yz1AcjN+28pPuGb9xexZHYz99/UVGVc2ndumm1/+Bs/nuhi9i4JIqLiy/pDysiIiIi9lIje7BWrlzJunXrWLNmDf/73/9wdnZmzZo1DBkyhLVr15KTk0NBQQEREREMHjwYs9nMgAEDWLFiBQCHDh3i2LFj9OzZsybCFRE7cndzoaGfNwWFRZxMTLV3OCIiIiKVYteDhgcOHEhUVBTjx4+nsLCQQYMGMXbsWACeeOIJ5syZw8iRIzEYDLzwwgu4u7tXuo9ly57TEsELSEk5xY49B9nw026CAv2Y+dDfK73Mb+feQ7z/6Ve0aRXC5Ek3XPT6oqIiBg+eQFZWNgaDAacGDcjLycFsNjN+/CgeeeT+SvV/KRYtepcPP1xFXl4+TZqH0qx1awry85l2/020btW82vuvq2pqXXXzpo1IPXWa47EJNG0SWCN9ioiIiFSFGk+wmjRpwp49e2yvJ0+ezOTJk8td5+fnx+LFi2sytHolKyubxx57lt27f6N1p054+vhitBRd0h6qsJbBAByLjqewsAgHhwt/W8XExNv22bUPD8fLx5e05GSOHYpk8+btl5Vgbd++l1de+R/Hj5/A29uTSZNuYsKE0WU+V1ZWNh98EIEVA36BgTRt2RKAowf289GHDjzxxD8vuX+pGqEhjdm++yDRsQkMuKabvcMRERERqTC7zmCJ/cyd+yK7dv0GBgMeXt5YLBa+WPMl3buE0b9/74s/4E/c3Vxp3KghJxNTOR6bQFjLphe83tPTnaKiIpqHtcHLxxcA34AAPH19Kc49S3GxBZOp8qtX9+07wD//OY/8/JLzk9LSTvPGG++SmZnFsBGDSUg6RUJSKkePn6DrNX0xO/xxvlVCbCzpqans33+o0v1K1Wse0giA6NiEcsVwRERERGozJVj10OnTZ9i+fQ+FhYUEhYRgMBpJT0kh62wWy5atrHSCBRDWsiknE1M5fDT2oglWw4a+dAnvhqN7SWJ3eN8+GgY1wi8gELO7N6/89yNuGjuo0kvDFi9+j/z8fJxdXPD198fNwwMXd3cOxKRw8L8flbnW7OBAYWEB2WfPkpl+mrjo4xgMBoKDgyr92aXq+ft54+rSgMysHNLSz+Dn62XvkEREREQqRAlWPXTmTCYmkwmDoYigpiXJUMrJk0DJrM+lCGsZwvebdnH46ImLXhsbl0QDL1+Kiy3EHjlMXvZZoiNPc1WnNmTmFxOfmMoriz/mmh6duX7o1TRwLtlDd/r0GYxGA56eHuWemZWdy+mzeXTq0QN3r7K/jFutVvx8PGnaJJCgQD+CAv1Y/u7H7Ni8hfz8Att1zs5O3HXXzZf0+aVqGQwGmoc0Yn/kcY6fSFCCJSIiInWGEqx6qEmTRphMJvwbN8apQQOys7JIT03FZDLRs2eXS3pmaEgQDmYTJxNTOZuVjbub6zmvyzybzdsfrqO42MI1PTrxyOSbOHUqnVatmuPm5kp+QSFff7+VHzfv5udt+/j14FGu6d6e99/9hJiYOABatw7lqadm4O/vx4FDx9mx9xCRUTEEhjQDoLioiFPJyZxJTycnKwtrcREbNnyMo+MfSwLnPfkIL764iC+//B6LpRhfXx8effQfdOjQ5pI+v1S90JDG7I88TnRMAj26trN3OCIiIiIVogSrHjKbzUybdg9f/1RSbCTu2DHMZhOuri7cddctl/RMBwczLZo34dCRWA4fjSO8S/lEpaiomHc++oIzmVmEhgRxw/X9MZtNZZblOTk6MHpYX8K7tOGT1d8RG5fE+u+3Y3L1wGgyk5+XR1xCCnPmv05AUBB5v89AGY0GGgf4sumHTSQnJGCxWICSWam///2GMskVgJOTI3PmTGPWrAfZsmUb/fr10T6fWsa2D+tEgp0jEREREak4JVj1lF9gIxydI7EWF+Hp6syg/iOYOHE8/v5+l/zMsJYhvydYsedMsFZ9sZHo2AQ8PdyYdMv1mM3nP0A2KLAhU++bwOIlH3Pw2Em8fH3p3KsnhQWFODVwBiAvv4DgIH/Cu7alW6fWuLu5ck14W15++X/Exsbj6enOHXeM57bbxp23H0dHR9zcXJRc1ULBQf44mE0kpaSTnZOHq4uzvUMSERERuSglWPVQUVERGzZuB+DO28bQpUOrKnluaXGLw0dPlKv8tmXHfjZv/xWz2cRdt47Ew/3cSwj/zGg0QFEB+7ZsIaRVK/wCA3FqYCI/L4/0lBQGD+jJvXdPKHPP1VeHc/XV4ao8dwUwm80ENwnkeMxJYk4k0L5NqL1DEhEREbkoJVj10NZdB8g4k0WjAF86tWtZZc9tFOCLh5sLmWezSUpJo1FAyWxYzIlEVn7+AwDjRw8kJLji1QHbtWuN2WTi6IGDJMSewGgykXXmDA0aONOty53nvU/J1ZUhNCSI4zEnOR6rBEtERETqhsofNiR1WlFREd9u3AHAdQN7lcwSVRGDwUBYqxAADh0pqSZ4JrO0qEUxfXt1pudV7Sv1zD59ehAUFICjowM5WVlknTmDo6MDLVs2o1u3DlUWu9ROzZuW7M+LjtU+LBEREakbNINVz2zdWTp75Vels1elwlo0ZceeSH7ctANLfi6/Hokj82w2LZo1ZuyIfpV+ntls4n//e5533vmEr7/+CaPRwPXXD+KOO27ULFU9UFro4sTJZIqKijCb9SNLREREajf9tlKPlOy9Kpm9GjawZ5XOXgEUFBTy3rJPMbh6cDozm/dWrMfLzw93Nxcm3XI9JtP5i1pciKurCw89dCcPPXT+JYFyZXJp4Eygvy9JKWnEnUyheYgOghYREZHaTUsE65EtOw9wJjOLoEA/OlbD7NUnn3zOgf2HycnKwmg04uXnh6W4mKSYWNzdXKq8P6kfQn9PqlSuXUREROqCCidYa9asOWd7dnY2Tz31VJUFJNWjsLD69l6V+uKLH8jPLyDzdIatLfbIMY4diSYt7XSV9yf1Q+ms1fEYJVgiIiJS+1U4wXryySeZPHkyqamptrbvv/+eESNG8NNPP1VLcFJ1tu760+xV2xbV0kfp4b7pKakUFxWReCKO9JRUDIY/3hOprD/PYFmtVjtHIyIiInJhFU6w1q5dS35+PiNHjuSjjz5i2rRpTJ06lRtuuIEvvviiOmOUy1RYWMS3P5acezWsmmavAIYO7YujowO52Tns/WUbCTEllQQbNfKnYUPfaulTrnwe7i44OTqQnZPH3CdeZceOX+0dkoiIiMh5VbjIRXBwMO+88w4zZsxg3rx5mM1m3nzzTa655prqjK/OKiwswmw21YpKd1t37ufM2WyCAv3oUE2zVwC33jqGzZt3cvJkMrm5eTg5OWI2m3niianV1qdc2YqLLcye/QIZuYW4e3sRefg4u3bsY9y467j33pvtHZ6IiIhIORVOsKKjo/n3v//Nrl27mDp1KpGRkfzjH//gvvvu45577sHR0bE646wzdu78jYULlxEfn4SzsxPjxg1l0qQbL7mC3uX6896r6py9AnBxacBbbz3PL7/s4sCBwwQG+jN4cB/c3V2rrU+5sm3ZspvIyKO4ennh7u2Fq4c76SmnWLlyPaNHDybg98OsRURERGqLCidYo0aNIjw8nLVr19K0aVOgZA/W/PnzWbNmDV9//XW1BVlXREYeY+7cl8nPLwAgNzePlSu/4uzZHKZNs0+J8S2/z141btSQju2qb/aqlNlsol+/HvTr16Pa+5Ir3y+/7CY3Nx+MWQC4uLsBYDQa2bPnAMOG9bdneCIiIiLlVKrIxbvvvmtLrgAGDhzI559/Tt++fasluLrmvfdWUVBQgMFgwMe/IU4NnMnPL+CrrzaSlZVT4/EUF1v+VDmwZ61YrihSGV5e7phMJvJycrBarTg5O4PBgNFowE2l/0VERKQWqnCCdeONNwKwa9cuPvvsM7KysoiKisLR0ZE5c+ZUW4B1SWzsSaxWCAhuTJMWzWjZsR3uXp6YzSZSU9NrPJ6o6EQyS2evqnHvlUh1GTasP2azCavVSuHvf7xwdHTEZDLRo0cXe4cnIiIiUk6FlwimpaVx//33c/ToUQoKCujRowevvPIKUVFRvPPOO2Vmtuqrli1DyMjMomFQIAAmk4lmbVqRfCKewMCa2Sty8OBRFi/+iGPHThDaPgyTg1mzV1JnNW0axIwZ9/Kf/yyhuLAQnJzw8fPmybkP4ejoYO/wRERERMqp8AzW/Pnzady4MVu3bsXJyQmAF198kbCwMB00/LvbbruBJi2aYzAYOJWUTHL8SQwGA4EhwWzYuAOLpXrP8Dl6NJaZM5/n4MGjuHl5YnIwk5eTy65t+6q1X5HqNHjwNURE/Jf27VoC8I+HJxEWFmrnqERERETOrcIJ1pYtW3j44Ydxdna2tbm5ufHII4+wZ8+eagmurklITaeBqwtWi4W0hCSKcnJp1TQQo9HI95t28d6K9RQWFlVb/8uWlewBMxqN+AUFAJAcl8DKlV+Rl5dfbf2KVLcGDZwJa9UcgNMZmXaORkREROT8KrxE0Gg0kpubW649NTXVNqNVn6WfzuSLDb8AcO8dY+jw7D9t7x06Ess7H33Bnt+iOJOZxd23jcbVxfl8j7pkx46doIGbG41Dg3H4/cDfsxmZNGjgTGpqOsHBjaq8T5Ga4uvjCUDa6TN2jkRERETk/Co8gzVy5Ej+/e9/c+jQIQwGA1lZWWzevJknnniCESNGVGeMtZ7VamXl5z9QUFBI5w6tyh3m26ZVCFPvG4+nhxvHYxN49c1POJVetb8k5uXlExjSmNB2rXBydiYvJ5f4ozEAFBcX4+vrVaX9idQ0Xx8PANLSNYMlIiIitVeFZ7BmzpzJyy+/zPjx4yksLOSGG27AZDIxfvx4Zs6cWZ0x1np7fovi4OFonJ0dGXf9gHNeExTYkOmTJ/C/5WtISDrFgsUfM2xADzZv2klSUiqdO7dl7NhBeHl5VLr/yKgYPln9HRajCavFQkpCMqcSkkvKWjs5Mnx4P1xcGlzmpxSxL7/SGawq/uOEiIiISFWqcILl6OjI7NmzmTZtGnFxcRQXFxMcHIyrq2t1xlfrZefkEbFuIwCjr+uLp8f5x8PL050p947nnY++4PDRE6z4/AcSY+LJyjjLsWNxfPXVJl5/fS5+ft4V7nv1lxvZsScSgODGAXRs3ZT3l6/GYABHRwf+9rfrmDhx3OV/UBE7c3N1wdHBTE5uHjm5ebg0qPpltiIiIiKX64IJ1o4dOy5488GDB23/7t69e9VEVMd8/tUmsrJzCG3WmF7hHS56vbOzE3f/fRQPPfI8Lh5uBDUPJvVkMmfSTpOVlc2HH65jypTby9xz5sxZFi/+mC1b9gLQq1cX+g3syfrvtnI2KwcHs4nhg3vT/+pumExGhg6+hoKCQn79dR/h4eHV8rlFaprBYMDXx5PE5DTST2cqwRIREZFa6YIJ1u23//GLfuk5SiXLzpwwmUzk5ORgMplwdXVl+/bt1RtpLXTkeBxbdx3AZDIxYewgjMaKnTV16tRpUuMTcfHyoGFQAP5NAvFvEkhRQSGHYxP4bN2PBDb0IdDfBz8fT/75z+dISUmnuLgYk9nE0bgkktZ8D0Bos8bcfMNg/P8y6+Xo6KCzr+SK4+tdkmClpZ+hSZC/vcMRERERKeeCCdaBAwds/46IiOCzzz5j/vz5tGrVCoDY2Fjmzp3LtddeW71R1kIFhUWsWP0dAEMGdCegoU+F73Vzc6G42EJ60ikK8wv4f/buOz7qIn3g+GdbNpveeyUEggm9KUV6FGkiIoLKHeop54Fy1rvT06VIG7EAACAASURBVNPz5+lZEBXFAnqKiiggvfcuoQdCTSO9Z1O3//5YWAihBAQSyPN+vXgRduc7M99JSL5PZuYZn0A/nJy1qE8fnLr59EzVGS5+PgS7umAyGHHzckelVmO1WumUEMv4sUMbHNgJcbOTTIJCCCGEaOoumUVQpVI5/kydOpV//etfjuAKIDIykldeeYUZM2Zc9442NavX76SwuIygAB8G3nllyyM9PNxo3z4OtVpFRamejCOpHN+XQtaxNLq3j2PYXb3o2rENEaGBKJUKVGoVLu6uePp5o1KrqdJXkp5yEieFQoIr0aycCbCudRZOIYQQQohrpcFJLgDy8/OJi4ur81pqaipOTk7XtFNNXU5eEWs37wZgzL0DUatVV1zHiy8+zhtvTOfYsXTUajVms5mhQ/rw4Oi76izt27w5iY8/mY0VBU7OWsxGE5XlFeh0WsLDg67ZPQlxM/D1lkyCQgghhGjaGhxgjRs3jhdffJHx48fTunVrAA4ePMjs2bN5+umnr1sHmwqLxUpq6inMZivLN+zAarXSs1s7oiNDrqo+d3dX3n33RbKz8ykuLiM6Ogx39/oZCG+/vQMzZ86juLiU6ooqAFQqJe7urtx+e4ffdU9C3GzOLhGUs7CEEEII0TQ1OMCaNGkS/v7+/Pzzz3z11VcAxMbG8uqrrzJixIjr1sGm4MiRVN5660sMBiMunm54+nvjotMy9K6ev7vu0NBAQkMDL/q+RqPmgw/+xqef/sDOnfsB6N69PU89NRaN5oomIIW46fl428+JKynVY7VaUSobfFa6EEIIIcQNcUVP6GPGjGHMmDHXqy9NUlVVDa+9Np2aGgMqjZrA079BzzqZhcloQuesve598PHx5JVX/ozNZgOQ7ICi2XLSqPFwd0VfUUVZeaUj4BJCCCGEaCquKMDavHkzBw8exGw2Ox72z3jmmWeuaceaim3b9jnu1S/YD6VKSVV5JdUV1WzalMTQoX1vWF8ksBLCvkxQX1FFcWm5BFhCCCGEaHIaHGC99dZbzJ49m7i4OFxd6+4VupUf/CsqqjCZLChVSlw93bBarRTlFGIxW9Drqxq7e0I0O77enqRl5FBcUk5si/DG7o4QQgghRB0NDrCWLVvGv//9b0aNGnU9+9PktG0bi1qtQuVkHypDtQGL2YKzsxNt28Ze5mohxLXm62OftZJMgkIIIYRoihq8Q9xisdCpU6fr2ZcmKTY2ki5d4nH1cAOgtroGrdaJ+PhYEhIkwBLiRnOchSWHDQshhBCiCWpwgPXwww/zySefUFXV/JbFvfDCBCKjQwEI9PPmySdH88orT9zSSyOFaKr85CwsIYQQQjRhDV4iuHXrVg4cOMDy5cvx9vZGo9HUeX/Dhg2XrWP27Nn8+OOPKBQKwsPDefPNN/Hy8uLtt99m8+bNWCwWHn30UcaOHQtAeno6L7/8MqWlpbi4uPDOO+8QExNzZXd4DVgsVsorqwH416t/xkXnfMP7IISwc5yFVSJnYQkhhBCi6WlwgDV69GhGjx591Q0lJycza9YsFi5ciLu7O++88w7Tpk2jdevWpKens2TJEqqqqhgzZgzx8fG0a9eO559/nj/84Q8MGzaMjRs38swzz7B48eIbPnN0KqcAi8VCcKCvBFdCNDJ3N1c0ahVV1TXU1hpwvgFHJQghhBBCNNQlA6xp06Zds4YSEhJYuXIlGo0Gg8FAfn4+YWFhrFmzhgceeAC1Wo2npydDhgxh0aJFBAYGkpqaypAhQwDo06cPr7/+OocPHyY+Pv6a9ashUjOyAYiOCLmh7Qoh6lMqFfh4e5JfWEJxqZ7QYP/G7pIQQgghhMMlA6ykpKQGVdLQGSWNRsOaNWt4+eWXcXJy4umnn2bVqlUEBwc7ygQFBXH06FFyc3MJCAhAqTy7TSwwMJC8vLwrCrCSk5MbXPZi9u5PAUBhM7J79+7fXd+NdLP1t7HIODVcUxgrtcr+92+79hAR6te4nbmEpjBWNwMZp4aTsWoYGaeGk7FqOBmrhpFxukyA9d13313zBgcOHMjAgQOZO3cujz32GGq1uk6AZrPZUCqVWK3WeoGbzWZDpVJdUXsJCQlotVe/hMhqtTFv+S4A+vftge/pDfY3g927d9O5c+fG7kaTJ+PUcE1lrNJzK8jOK8HLx69J9OdCmspYNXUyTg0nY9UwMk4NJ2PVcDJWDXMrjpPBYLjiCZsGZxH8vTIyMurMiI0aNYqcnBwCAgIoKChwvF5QUEBQUBAhISEUFhZis9nqvXcjFRSVUF1Ti6e7Kz5eHje0bSHEhfl6y1lYQgghhGiabliAVVhYyLPPPktJSQkAixcvJjY2lsTERObNm4fZbEav17N06VIGDhxIUFAQERERLFu2DIDNmzejVCpp1arVjeoyAGkZOQBER4VIWnYhmgi/M2dhSYAlhBBCiCamwVkEf68uXbowceJExo8fj0qlIiAggOnTpxMcHExmZiYjRozAZDIxZswYunXrBsAHH3zAP//5Tz777DOcnJyYNm1anT1ZN0LqmQBLElwI0WQ4UrWXSqp2IYQQQjQtNyzAAhg3bhzjxo2r9/rLL798wfJRUVHXZR/YlTgzg9UiMrRR+yGEOMvn9F7IklI9Vqv1hv/iRQghhBDiYuSp5BL0FVUUlZTj5KQhJKjpZioTornROmlwd3PBYrFQrq9q7O4IIYQQQjhIgHUJZ2avosKDUalkqIRoSs4sEywplX1YQgghhGg6JGq4BMf+q8jgy5QUQtxoZ45MKJIASwghhBBNiARYl5Aq+6+EaLIciS5KJNGFEEIIIZoOCbAuwmA0kZ1bgFKpIDL8xp69JYS4PF8fOQtLCCGEEE2PBFgXkXEqD6vVRkiQP85ap8bujhDiPH7eZ1K1S4AlhBBCiKZDAqyLOJueXc6/EqIpOrtEUAIsIYQQQjQdEmBdRGpGNgDREmAJ0SR5uLuhUqmoqKzGYDQ1dneEEEIIIYAbfNDwzcJqtZJ+Kg+A6AgJsIRoipRKBb7eHhQUlVJSWk5woJxV11gsFgtmqxWrzXbF1waGhFBjNF6HXt16ZKwuTgGolErUKlVjd0UIISTAupCcvCIMBiM+3h54ebo1dneEEBfh6+NJQVEpxSUSYDWWGqORsupqTGYzVx5eQW5RERaN5pr361YkY3VpaqUSV2ctnp6ejd0VIUQzJwHWBcj+KyFuDo6zsGQfVqMwms2UVFZitlobuytCYLZaKa+uQa3TNXZXhBDNnOzBuoDUzNMHDMvyQCGaNEeii1I5C6sxmE4vDRSiKak2GK5quaoQQlwrEmBdgGMGK0oCLCGaMjkLq3GZLZbG7oIQ9ZgtFmwS+AshGpEsETxPaZmesvJKdM5aAv19G7s7QohL8JNU7aKJSOzZk7c//JBOXbtetuzJY8eorq6mbYcON6BnF/ftzJnMnjWr3usKhYKVW7bw/KRJHNi7t9777Tt14t2PP673usVs5ttZs1i9fDmGmhp69+/PxKefxtnZGYDS0lJmTJvGnl27ALi9Z0+enDwZN3d3AA4nJzNj2jTSTp7EPyCAsX/4A4MGD3bUv3f3br785BOyTp0iJjaWiU8/Tes2bS54bzJ/JYRoTDKDdZ7UjDPLA4NRKhWN3BshxKX4nN6DVVJajtUqj1Ti5vCvf/yDrMzMxu4Go8eOZc6iRY4///v5Z/wCAhj14IMAvPrWW3Xef2faNFQqFfeNGXPB+r6dOZOlv/7K5Gef5b3p08k+dYq3X3/d8f7b//oXRYWFvD11Kv/33nuknTzJB//5DwBlpaW88vzzdOzShS+++46xf/gDU99+m+T9+wHITE/n5WefpVPXrkyfOZM7evXipaefprCg4DqPkhBCXDmZwTrPmeWB0bI8UIgmz1nrhKuLjqrqGioqq/D0kKyf4ibQRPYH6Vxc0Lm4OP79xSef4OLiwqMTJwLg4eHheM9ms/HaSy8xaPBg7ujV64L1LfzlFx7/y1+4o3dvAP726quMGzmSUxkZOOt07E1KYuYPPxAeGQnAn6dM4bmnnqK2tpaC/Hx69O7NhCefBCA4NJQFc+dycN8+Etq3Z/H8+cS2bs3jTz0FQHhkJPt272bRvHk89uc/X/vBEUKI30ECrPOcmcFqIQkuhLgp+Pp4UFVdQ3FJuQRYTcDh5GS+mj6d40ePgkJB2/btefbvf8fH15eHRo5k/GOPMXj4cEf5v0+Zwn0PPMDwUaNI3r+fzz/+mLSTJwkOCWHMI48w8O67AXj3zTex2WyknTxJYUEB7378MSq1mhkffcSh/fsxWyy0iovjmRdeIKpFCwCOHTnCJ++/T+qJE7Rs1YqOXbpwcP9+3vvkE4BLtne+5ydNol2HDuzbs4djKSnExsUx5cUXiYyOrle2uKiITz/8kL1JSRhqa4mIiuLPU6bQrkMHnp80ify8PKa+8w7JBw7wwiuvkJ6ayvSpU0lJTsbP35+hI0cy6sEHUSjsqyh+mj2bpQsXUlhQgKenJ4OHDeMPf/qTo1/x7dox4YknAMjLzWX8/ffz9U8/ERoWxrtvvkl+Xp7jni8mPy+Phb/8wmv/+Q9qdf1Hgw1r1nAqI4M3/vvfC15fVlpKdXU1tyUkOF7z9ffH08uLlORkevXty5vvvktoeLjjfYVCgdVqxWQ00ioujudffhmwn0W5c9s2TmVm0q5TJwByc3Joc07dAC1atiTl0KFL3pcQQjQGWSJ4jppaA7n5RahUSsLDghq7O0KIBjiTSbCoVPZhNbbqqir++fzzdOzalS9mz+btqVPJzcnhh//9D6VSyZ39+rF540ZH+bTUVPJycujdrx8lxcW88vzz9E9M5PPvvuOhCROYPnUq27dscZRft2oVD02YwP+9/z4RUVG89tJLBAYG8tk33/DhjBlYLRa+nD4dgKrKSl5+7jlatmrFp998Q79Bg5jz3XeOuhrS3vl++v57et55J59+/TV+/v68/NxzGA2GeuX+++9/Yzab+XDGDD79+mv8AwL46N13AfuyO7+AAJ6YPJmnpkzBYDDwj+eeo018PJ9/+y1P/fWvzJ87l4W//ALAmpUr+eXHH/nrSy/xzkcf8fCECXz/zTccOXy4QZ+Tp6ZM4dW33rpsuZ+//54WsbF0u+OOC77/47ffMnTkSLx9fC74vru7O2q1mqJzluzVVFdToddTXl6Oi6sr3Xr0QKk8+9ixYO5comNicD9npsxgMDCkb1/7bNnddxPfti0A3j4+FBUW1mkzPy+P8rKyy96bEELcaBJgnSM9MxebDcJCAnDSyOSeEDcDP29JdNFU1NbW8uD48Tw8YQLBISHEt2tHrz59yEhLA6DvoEHsS0qiqrISgM3r1tEmIQFvHx8WzZtH+06dGPnAA4SGhdF34EDuGzOGBXPnOuqPiY2lV58+tG7TBqPRyOBhw3hi0iRCwsKIbd2aQffc42hrw9q1OGm1/OWvfyUiMpIR999P7379HHU1pL3zdenWjVEPPkhEVBR/feklKvR6du3cWa/c7T172tuNiiIyOprho0aRmZ6OzWbDw8MDlVKJq4sLrm5urFu1Cg8PDx6dOJHQ8HC63XEHf/zTnxz98PPz47l//IOOXbrgHxDA0JEj8fH1ddzn5bi6udVZ6nchNTU1rFm5klEX2VuVvH8/pzIyGHH//RetQ6VW07tfP2Z9/jl5ubnU1tby6bRpAJhNpnrl582Zw+b163ly8uQ6ryuAj778kpdefZV1q1fzy5w5APQZMIAtGzeyef16LGYzO7dtY8eWLZjN5kvemxBCNAaJIs7hWB4YGdrIPRFCNJTjLKwSOQursfn4+pJ4zz3M++knUo8fJyMtjdQTJ4iLjwegTXw8fgEBbN+6lYF33cWm9esZeDpLXGZGBrt27GD4wIGO+iwWC55eXo5/BwYHOz7W6XQMGzmSNStXcuzIEU5lZHDi6FE8PO1fD2knTtAyNhbVOcvd2iQksPX0DFpD2jvfbadnUwBcXF0JjYggMz2dnnfeWafc0JEj2bBmDYcPHuRUZibHjxwBwGqx1OkPwKmMDNLT0ur0w2a1YjKZMJlMdOjcmZRDh5j52WccP3qUrMxMSoqLsV7DFPlJO3aAzUaP8+7jjI1r19Khc2f8AwIuWc9TU6bw9uuv84fRo1FrNAy9915iYmNxcXWtU+6XH3/ky+nT+ctf/1ov66KTVkts69bEtm5NYUEBC3/+mfsffJAu3bvz6JNP8s4bb2A2m2nZqhXDR41i3+7dv+/mhRDiOpAA6xyOBBeRwZcpKYRoKs4eNiwzWI2tqLCQSY89RkxsLF26d2fwsGH8tn07yQcOOMr0HTCALRs20DI2lpysLLp07w7Yg5u+Awfy0IQJdeo8d0mZk5OT4+Oa6momPf447h4e9Ojdm34DB3IqI4OfZs8GQKVSYTs/mcQ5/25Ie+dTqVR1/m21WOqVt1qt/G3KFCr0evoOHMjtvXphMpl44x//uGCdFrOZ9h078vQLL1ywveWLF/PZtGkMHjqUzt27M/n553nhnFmf83PdWq4i8Nq1YwfdevSoM77nv3//uHGXrcfTy4v/TJ1KZUUFSqUSF1dXRg8ZUicw/varr5j99dc8NWUKw0eNcryenZVFfm5unYArMiqK8vKz/68feOgh7hszBn15OT6+vnw5fXqduoUQoqmQAOs0i8VCRlYeAC0iL57gwmazUVVVg8VixmZr2mncnZ1dKCuraOxuNHm30jgpFDZUKjWurjrHBvlbna8sEWwytm7ciIuLC//3/vuO1xbOm1cn0Ok7cCBTJk4kukULOnfvjqubPTFJeEQEB/ftIzQszFF20bx5FBcVOTLLnWv/3r0UFhTw+bffOpIy7P7tN0dbkS1asHXTJiwWiyMwOn70qOP6K20P4OTx446PqyorycnOJjompk6ZjPR0Du7bx48LF+Lr52evd/584Jyzmc75vxkWGcmWTZsICgpyzG5tWr+e3Tt38te//Y0lCxYwdvx4xo4fT25uLu5ubpSVlDjqUms0VFdVOerLzc6+YN8vJeXQIUacE+ycq7ysjJzsbNp17HjZev7773/Td8AAuvXoYa83Odme+OL0zN+CuXP5/ptveObFFxkyYkSdaw/s2cOszz/n+wULHIHe8aNHiTidcXD9mjUc2r+fSc89h4+vLzabjZ3btjH8vvuu+H6FEOJ6kwDrtKycQkwmMwF+3ri5ulywTHFxGceOpVFYWHpTrPsuKCggIOBUY3ejybvVxkmtVuPv70OrVlH4+l58udOtwsvTDaVSib6iCqPRhJOTprG71Gx5eHpSVFTE7t9+IyQ0lE3r17NlwwZiYmMdZVq0bElgYCDzf/qpzqzNsPvu49eff2bmZ59x99ChnDxxgi8//ZQnJk26aFuG2lq2bNhAXHw8e3ftYtG8eWhPH2rbb+BAZs2YwYxp0xwZCjesWeNImnCl7YF9qVzHzp2Ji4/nmy+/xM/fv94SNzc3+9fjxrVr6dmnD0dTUvhu5kwATEYjarUanU7HqcxM9Ho9AxIT+W7mTD54+23GPPwwhQUFfPL++yTec4/jPvft3k2vPn04deoUi+fNw2w2YzIaAWjVpg1LFixgwF13oVQq+W7mzDq/XKmqrMRitV50H5bFbCYrM/OC2RAB0lNTUavVhJ2T/e8Mg8FAVWUlPr6+jr5+/cUX+Pr7YzQaeeeNNxgxahQeHh4U5OXx1WefMXTkSO7o1YuS4mJHPZ5eXvTq25f/ffUVH7/3HmMefpgjKSn8MmcOf3vtNQAiIiJ47803iW/fntZxccz57jtqa2oYdHqchBCiKZEA6zTHAcMXmb3S6yvZuXM/xcU3T8Yivb4SV1f3xu5Gk3crjlN5eQWlpeX07t0Fd3fXy19wE1Mqlfh4e1BUXEZJmZ6gAN/G7lKzdWf//hzct4//e/VVAFrFxfHk00/zzeefYzAY0Gq1gD3ZxZxvv6VH796UnV4CFhgUxL/ffZeZn33G/J9+wtvHh/GPPcawkSMv2NZtCQk8/OijTJ86FZPRSFRMDJOfe4733nqLgrw8AoKCeOO//+Xj995j2aJFtGrThgF33eXIRHel7QH0GzSI5UuW8PH779O2Qwf+M3VqvZTm/gEBTH7+eb7/5hu+/uILwiMieGrKFN59801OHDtG2w4dGD5qFF9+8gl5OTm8+tZbvPXBB8z46COemjABN3d3Eu+5x5F2/c9TpvDBW2/x1IQJuLq703/QIHQuLpw4PZs26sEHST95kuf/8hf8/P158umnef2c5YiffvjhJdO06/V6LBZLnUx+5yotKcH1dNB4vo1r1vDeW2+xautWAP7wpz/xyfvv88LkyTg5OTFo8GD+ePo+tm/ZgsloZPH8+Sw+PaN3xpmU8v/58EM+/eAD/jxhAt4+Pvz5mWfocfpMrZhWrZjy0kt8/fnnlJWWktC+Pe989BE6ne6iny8hhGgsClu9Req3BoPBQHJyMgkJCY4f6pcy64clHDh0grH3DaJ75/h676enZ7N5c9L16Op1k5ubS7CsT7+sW3mc+vTpSsQ1PNNt9+7ddO7c+ZrVd6189vV8jp7I5E+PDCc+rkVjdwdoumN1LZVXV1NWXf276rhe//9yc3IoLiwkoX17x2sfv/8+tTU1vPDKK1dc3/nnTTWGW/l71bVUXlrKbS1aoD5vz5yorzl8n7pWZKwa5lYcpyuNKUDStAP2fVWp6ZeewSotlQxl4ubTXL5uHWdhyT4scVp1ZSUvPfMMm9avJz8vjy0bNrB2xQru7N+/sbsmhBDiFidLBIGi4jIqq6pxc9Xhf5E9K1eTmUmIxtZcvm79JJOgOE9Mq1ZMevZZZs2YQWFBAQGBgTw5eTLdTydgEEIIIa4XCbCA1MzTs1cRIc0m89rv8eabLzJu3J9o0SL2smXz8nIwGg1ERFx4A/WNlJWVwerVi8nPz8XDw5NevQbQrt3Zaey0tBOsXbuE4uIiAgNDSEwcRkjI2Y3dW7euJylpGzU11URERHP33SPw8fG/aHtbtqxj9+5tGI1GYmJaM3jwSHQ6ewIVg6GWlSsXcvToIdRqNR07dqdPn0TH119+fg7Lls0nPz8XP78A7rnnvjp9OWPz5rUUFxdw771jr9Uw3ZTOZhJsHjN2TYWyiX+/HDx8OIOHD78mdV1sD5NoepQKhfwsF0I0KlkiCKSdXh7YIura7VURdj///D+KiwsauxtUVVUyZ84soqJa8uSTz9Kr1wCWLPmFzMw0AIqK8vnxx5lER7fi8cefplWr25g9+wv0entSk717d7Jjx0aGDr2fJ56YgrOzjjlzvsZms16wvZ07N58uP5rx4ydSUlLIypULHe8vXPgTBQV5PPLIRIYPH0NS0jb27fsNAKPRyI8/ziQ0NILHH3+aiIho5syZhcFQW6eN5OS9bNq0+noM103n7GHDMoN1Izmp1fIgK5ocnZMTqkucZyaEENdbs/4OZLFYOJhykkNH7Q/Z0dcwGYBoWvT6Mlq1iqdfv7vx9valXbvOBAQEOgKspKTtBAeHMmDAPfj6BtCjR1/CwiJJStoOgNFoYMCAIcTEtMbHx5+ePftTUlJEZWX987NsNivbt2+gf/97iIlpTWBgCAMGDCE/PxebzUphYT7Hjx9m5MixBAWFEBPTmu7d7yQ7254q/vDh/SiVKgYNGoqfXyCDBg1Dq3Xm8OH9AFitFpYtm8+SJT/j7e1zg0awaTsTYJWUltc/XFZcNxqVCg+dc73DboVoLFqNGo0E/UKIRtZslwgWl5Qz7Yu51NTWYjLZ96ksW7ONJ8bfi1rdsMxDWVkZrF27lNzcbBQKCA+PZujQ0bi7u/PRR29x552D6Nixu6P8jBnv0aVLD7p06UFmZhpr1iyhoCAXLy9fevTo61iutmjRT9hsUFCQi15fxiOPPIlSqWL16sWcOpWGxWIlODiMIUPuw98/CIDc3CxWrPiV/PwcgoJCiYpqyYkTR3n88acBLtne+b79dgaRkS1ITz9Jbu4pgoLCGDJkFP7+gfXKVlToWbVqIWlpJzCZjPj5BZKYOJzIyBZ8++0MystLWbp0HqdOpTN8+BgKC/NYsWIh2dkZuLt70rnz7XTvfqfjt+Dbtq1nz56d6PXluLi40KFDN/r2vcvRr/DwKPr1uxuAsrISPvnkbZ566kV8fPxYtOgnyspKGT9+Yr1+BgeHMXz4A4A9ADp+/AjFxYVERrZw1BUWFlnnmsDAELKyMgDo3v1Ox+u1tTUkJW3D3z8QN7f66d0LCwuorKykTZu2jteio2N58slnAUhPP4G/fxC+vgGO93v3HuD4ODs7g/DwKBQK++8/FAoF4eFRZGVl0rFjd4xGI8XFBUyYMJmdOzdhtV54Fq050TlrcdE5U11TS2VVNe5ut3Zq+qZCqVTi7qxDq9ZgMJmwXGRG91K83d1xc25YVqbmTsbq4hQo0KrVOGk0HEpLJ+IC53YJIcSN0mwDrP/NWYa+ogqbzYZCobBnEszIYf3WPQzq0/Wy1xsMtcyZM4tu3XoxfPiDVFbqWbx4Llu3rmPw4JG0adOOI0eSHQFWQUEexcVFxMW1pbKygjlzZtG37120bDmW3Nwsli2bj7OzjlatbgMgOXkPo0Y9goeHJ35+gcyY8R5RUTHcdddfMRhqWLHiV9asWcrYsY9RW1vDjz/OJC6uLcOGPUBa2nFWr15MQIB9Rq4h7Z1v27YN9O9/N0OG3MemTWv48ceZPPXUC6jVdQ9xXbhwDk5OWv74x6ew2WDdumUsXz6fiROfZ/To8XzxxVS6d+9Nhw5dMZlM/PDDTNq27cSQIfdRUlLM0qXzUKnUdO3ak4MH97BjxyZGjhyHt7cvJ08eZfnyBcTGtiE0NOKyn5PExOGXnb0wmUy8++4/sVqtdOp0O+HhUeTm5uLq6oZeX3d5WXl5KTU1VXVe27NnB8uWzUelUjNu3GOOIOhcpaXFaLVacnOzWL9+OZWVFbRo0ZrE6KCmRQAAIABJREFURPtMVGlpMV5ePuzcuZmkpG0AdOjQjR49+qJQKKisrMDXt+7eLldXd/Lz7UtZnZ11PPJI/SCyufP18aQ6u5aiknIJsG4glVKJzskJnZPTVV2fn3kKX7eoa9upW5SMVcM0l+Q+Qoimq1kuEayorCYrt7Dew7jJZGZHUnKD6jCZTPTs2Z/evQfi7e1DeHgUcXFtKSzMAyA+vgNpaSeora0BICXlAFFRMbi5uZOUtI2oqBi6deuFj48f8fEd6N69N7/9tsVRf1BQCHFxCYSEhGM2m+nQoRsDBw7Fx8eX4OAw2rXrQmFhPmBfUqZWa7j77hH4+QXQtWtP4uLOzp40pL3zxcS0onv3O/HzC2TIkFHU1lZz8uTReuVatbqNu+4agZ9fIP7+gXTp0oOiogJsNhs6nQtKpRKtVouzs47k5L3odC707z8YHx9/WraMo2/fu9i5czMA7u4eDBs2mujoWLy8fOjc+Q7c3Nwd93k5zs46RxKJi1EoYMKESYwY8SCHDu1jx45NANx2WweOHEkmJeUgVquF48dTOHbscL0f1C1atOaxx56mQ4euzJ37P0pLS+q1YTQasFjMrFmzhL59B3PvvePIy8tm4cKfHO9nZJwkLe04I0eOo1+/wezYsdHx+TCZTKhUdX/3oVKpMJvNDRqH5srXx35QqiS6uLnU1NQ0dhduGjJWQghxc2iWM1hWq5WLLdFu6G++3Nzcad++Czt3biY/P4eionzy83MJCbHPtISGRuDh4cnx4ym0bduJlJQDjmVmRUUFnDhxlHfeOXvYpdVqxcXl7G/dPT3P7q1xcnKiS5c7OHhwDzk5WRQXF5CXl41OZy9fUJBHUFAISuXZpY1hYZGUlBQ3uL3znbtcTqt1xsfHn6KiAlq3rluuc+fbOXRoP1lZ6RQVFZKXlwXYl+EpFHWXWhYXF1BYmF+nHzabDYvFjMViJiqqJdnZmaxbt5yiIvs9VlZWXDSRxNVQqzUEB4cRHByGXl/Orl1biYyMJSamFf363c3ChT9isVgICgqla9cepKefqHO9l5c3Xl7eBAWFkpFxkgMHkujTJ7FOGaVSidlsZtCgYURH2zMtDhkyilmzPqaiQo9SqcRisTBy5Di0WmdCQsIpLy9l9+7tdO/eG7VajcVSN5iyWCxoNHVnD0VdZzMJSqILIYQQQjSeZhlgebi74u3pTmFxmWN5INhnCTq1bX2Zq+30+nJmzfqIwEB7koKOHbtz4kQKmZnpjjK33daeI0cOEhQUQklJMXFxCYA9uImP71Bn3w1QZ7mZWn32U2M0Gpg582N0Oh2tW8cTH9+B4uICtm3bANgf6C+1NK4h7Z1PeV4GJnvApKj32vfff0lNTQ3x8e2Jjb0Ni8XCL798e9F+REa24J577rtge3v3/saqVYvo2LEbcXEJDBw4hO+++/yc/tavr6FKSoooKyutk1re3z+A6uqzSwB79OhL9+69qampxs3NnbVrlzoC3dTUY3h5+eDj43e6Lwp8fQOoqamu15abm30m5dw9VmeW/On1Zbi5eeDu7oFW61zn/TMZC93dPeolz6isrHDUKy5MzsISQgghRFPQLJcIKhQKQoL86gQMWicNfj6eDOrXrUF1HD2ajJOTlrFjH6Nbt15ERESfXi52NtCJj+9AaupxDh3aT0xMK8fyNV9ff0pKCvHx8XP8SU095kjTfb6MjJOnk11M5I47+tKiRezph3F7W35+geTn59YJOHJzsxwfX2l7AHl5uY6Pa2trKCkpJiAguE6ZwsICMjPTGDfucXr1GkBsbBsqK+3Lsy4U79n7UYSXl7ejH/n5OWzbtgGFQsmePdvp1as/iYnDadeuMy4urlRVVTrqUqnUGI0GR30XWp53MRkZJ/n11x/qLLPLzc3Gz88eBB06tI8VK35FpVLh5uaOzWbj+PEUoqJiANi0aQ27dm11XGu1WsjPz3Fcf66goBBUKjV5edmO14qKCgAFnp7ehIVFUl5eVie4KyrKdwRzoaGRZGVlOIJmm81GVlZ6g/ahNWeSql0IIYQQTUGzDLAOHj7JgcMnUamU9O3Zid63t+fB+wbx4uSH0TUwQ5NO50JFhZ7U1GOUlhazbdt6jhw5WGdpV2BgMJ6e3vz222Zuu6294/XOne8gPz+HdeuWU1JSSErKAdauXYqHh+dF2nLFZDJx5MhByspK2Lt3J7t2bXMECwkJHTCZjKxatYji4gL27t3JoUP7HTM+V9oe2Pd17d+fRFFRPkuW/IKHh6djudsZzs7OKBQKDh/eT1lZKSkpBxznMp0ZBycnLcXFhdTUVJOQ0BGLxcySJb9QVJRPauoxVqz41RF46nSupKWdoLi4gNzcLObP/x6r1eKoKzg4jOTkvWRnZ5Kbm8WmTavgnATRtbU1F5xRAoiLa4tSqWT58vkUFxc6Emr06mWf1fP1DTg9bvtOJ9/4BaPRSLt2XQDo2rUHe/bY3y8qKmDp0vlYLBZHJkaj0UBVVSVgX1LZufPtrFq1iMzMNHJzs1i+fD5xcfG4ubkTFdWSgIAgFi6cQ2FhHsePH2b79o106XIHAG3atMVoNLBy5UIKC/NZvXoxRqOB+Pj2F7gzcYZjiaDMYAkhhBCiETW7JYLl+irmLLAHAcPu6kXfnp2uqp7bbmtPZmYa8+d/D9gf/gcNGsaGDSswmUyO/TLx8R3YunUdrVvHO6718vJmzJgJrFu3nJ07N+Hq6s6ddybSufMdF2wrLCySO+8cyMqVCzGbzQQEBDF48EgWL55LeXkpnp72+pYvX8DevTsJDg6nbduOFBUVXlV7YA/a9u79jeXLFxAREc3YsY+jUtXdU+Xh4cXgwSPZvHktGzaswNfXn8TE4SxaNJe8vBwiIqLp0qUHa9cuoayshPvvH8/YsY+xatVivvpqGs7OOtq160K/fvY07ImJw1my5Ge+/HIaLi6u3HZbO5yctOTl2bPn3X77nRQW5vHddzNwd/dk0KBh/Pzz2eWIq1Ytumiadp3OhXHj/sTKlb/y1Vcf4urqTmLicFq3jic3N5egoBCGDLmf9etXUFVVSURENA8//AROpzOjxcd3oLa2lg0bVlJRUU5YWBQPPfQ4Tk72gHz79o0cOLCbyZP/DsCAAUNQKpX8/PP/sFgstG6dwN13jwDsyyHHjJnAihW/MmvWx2i1znTvfidduvQA7AHagw8+yrJl89i79zcCA4N58MFH6ywpFPV5ebqjVCoo11diMpnRaJrdtzchhBBCNAEK2y16KqfBYCA5OZmEhAS0WvtDsNVq4/P/LeDoiUxat4zgyT+MRKls2IGESUnJpKScvJ5dvmqlpSVUVJQTERHteG358gXo9eWMGfPHK67v/POmbnW5ubkEBwdfvuBNKD6+JZ06xV++YAPt3r2bzp0vfH5aU/Dv97+muKScv08ZT6B/4x7C3NTHqqmQcWo4GauGkXFqOBmrhpOxaphbcZwuFFNcTrNaIrh5xz6OnsjE1cWZcaMSGxxcNXUGQy3ff/8FKSkHKCsr5ciRgxw8uIeoqNjLXyxucbfG13hDSSZBIYQQQjS2ZrOGJievkEUr7OcMjRk5EE8Ptyu6Xq1WXb5QIwkKCuHuu+9l3brl6PXleHp6MWjQUIKCJClCc9eUv26vB18fDzgJxaVyFpYQQgghGscNDbAWLlzIzJkzUSgU6HQ6Xn75Zdq2bcvnn3/OggULsFgsDB8+nEmTJqFQKCgpKeHFF18kJycHpVLJG2+8QadOV75nymQy893cFVgsFu7okkC721pecR2+vl4oFBfOjtcUdOzYnY4du9d5LTc39yKlL+1Ce5jEzUehUODjc/FEJrciySQohBBCiMZ2wwKs1NRU3n33XebPn09AQAAbN25k8uTJvP766yxfvpz58+ejUql47LHHiImJ4Z577uH111+nS5cuTJw4kZSUFJ544glWrVqFTqe7orYXr9pCbn4x/n7e3Dukz1X139vbk8BAf/LyCq/qeiFutOBgf7y9m9fZWX6yRFAIIYQQjeyGBVhOTk68+eabBATYzw1KSEigqKiIFStWMHToUFxc7Km677vvPhYtWkRiYiIbNmzgtddeA6BNmzZERUWxefNmEhMTG9zuibQsNm3bh1Kp5JHRd6N10lxV/93cXOjevS3p6Tnk5BRgNpub7GzWGWazAS+v5vWAfTVupXFSKECj0RASEkBkZAiuri6N3aUbyvc6HDZcazCyeecBDh45iUaj5o7O8XRq2xrl+SdfCyGEEEJwAwOssLAwwsLCAPvBqf/5z3/o378/BQUF9OrVy1EuKCiI/Px8SktLsVqt+PiczQQWGBhIXl7eFbU7b/F6ANq1iaAwP4vC/KzLXHFpWq2WqCh/bDZo6gkYY2KCGrsLN4VbaZwUCgUKBZjNRo4fP3pd2ti9e/d1qfdaMBhNABQUlZKUlFTnMPGrYbFYWbPjMFU1BqxW+//3X5dvJmlvMl0Toi9zddMeq6ZExqnhZKwaRsap4WSsGk7GqmFknBohyUV1dTV/+9vfyMvL46uvvmLKlCl1HoJsNhtKpRKr1Vrv4chms9U7i+lyDEYTEWGBjH9wOEpls0qaeEumyrweZJwarqmPlc1mY+Hq3RgMJjx8AoiNDv9dQdbuA0cxGM1YLFZsVhsKhQILVrILyrg/uiV+l9jj1tTHqqmQcWo4GauGkXFqOBmrhpOxaphbcZzOpGm/Ejc0wMrJyWHixInExMTw7bff4uzsTHBwMAUFBY4yBQUFBAUF4evri81mo6ysDC8vL8d7gYGBV9yuFVuzC66EaG7MZgvf/7oKs9kCwLe/rCAkyI8JDwxB51z33AqzxcLqzbvYtS8Fo8lMeEgAwwb2JCTQD7CfmZeTV8jGbXup0FdhtVgd12q0Gpw0ajKz8y8ZYAkhhBCiebphUUdlZSWPPPIIiYmJTJ06FWdnZwAGDBjAokWLqK6uxmg0Mn/+fAYOHIharaZv377MnTsXgCNHjnDy5Em6d+9+qWbq0Wg1VFTVSNpmIW5x67btJjUzx74RDTAZzeQVlLBw1ZZ6ZecuXseOPYcwGE3YbDYysvKY8d2vrN7wG9/8uJR//udz3pv+A5mn8hzB1ZmZMJPBRE11La66hh02KIQQQojm5YbNYH3//ffk5OSwevVqVq9e7Xj9m2++ITExkdGjR2MymRgwYAD33nsvAK+99hqvvPIKQ4cORaFQ8N///hd3d/craletVmO2WDGbzdf0foQQTUvSgSOYzRaUSgUWwFhrxGQwsSvpEMWFZThp1Gg0amxAyvF0rDab/egFqw2L2YrNZmPp6m2O+ry93IkMD+ZoaqY9oY0CLCYLJqMJo8HEklXb8PP1chxuLIQQQggBNzDAevLJJ3nyyScv+N7EiROZOLH+2Ut+fn7MmDHjd7etddLg7+f9u+sRQjRdZ5YGKtUqMJrPSURj43jqqctXoAB3Nxfu7nc7rVpG4OfjiUKh4ERaFj8tXofRaMKqURPg701lRTWnsvN575MfeOj+u0ho0+L63pwQQgghbho3PMnFjabWqBg9dICkVBbiFhcbHc6hY6moNSqU7jqw2bDZbPj5eDF0QA/MZjNGk5nyiipWbtiJ1WrFZrOvKFSqVajVSrp1jKdn93Z16m0ZHcbfJz9CUXEZGo0ab093qqpr+eGXlRw6msZXsxfRv3dnhgzqiUolez2FEEKI5u6WD7AeHzsUPx+ZvRLiVje43+2kncrBaDRhMltQq1SoVCrGjRzkSF5xRm5hMUdTMx2zXgAatZqeXdpesG6lQkHAObPgri7OPPbwcDZs3c2SVVtZt3k36afyuG9oHw6fyCA7vwiFxUR0y1b4eF7ZsmYhhBBC3Nxu+QDLvZkdtCpEc+Xl4cZfHx9D0oEjnMopINDfm67tb8PDrf73gAeG9b9gFkGfKzhwWqlU0L93FyLDg/nfnGWkpmfz/qc/4ubhilKjQgF8NvtX/jjqbkKD/K/hnQohhPi9qmtqsQGuOufG7oq4Bd3yAZYQovnQOWvp3a39ZcupVSoG972dwX1v/91txkSF8sKkh/jvJ99TUVFFRVklWhctWhctRpOZxWu3MfGhEb+7HSGEEL9fcameeSs3kl9YCkCAnzf33dUbfx+vRu6ZuJXIhgEhhPid3N1c0Lg4oXWxp243VBuoqajBZrORV1SC2WK5TA1CCCGuN5PZzMyfl5GTX4zFasVitZJbUMysn5djNJkau3viFiIBlhBCXANarRPOrs64eLqAwn5eVrW+GoVCIQedCyFEE5ByIgOz2YzNZsNQY8BQbcBms2GxWDh0PL2xuyduIfJTXwghroGu7VqjVqvQOGlw9XQFBZiNZlQWsMoMlhBCNLoyfRVGk4maihr7n8oaKksrqakxUK6vauzuiVuIBFhCCHEN9OnWgbgWEahVKlxddbh7u6FSKSkqKmPW90swmeSwcyGEaEx+3h5Ul1djrDUCoFAqsJgtVJRUkJtbiMVibeQeiluFJLkQQohrQKVSMvqevpTpKyksLiMnO5OWMbF8Oms+h4+l89XsRTz20DCcnDSN3VUhhLgp6Cur2LonmfTsfNxdXejRMZ4W4cFXVVe5voqlK7diNJhQKBW4erqiUqmora7FUG1gZ9Ih8vKLGTcqkUB/n2t8J6K5kRksIYS4hrw83IiNDsNNpyU02J9Jj4/CzdWFoycy+fK7hRiMspFaCCEuR19ZxRdzl7L38AmKy/SkZ+fx84oN7Dl8/Irryiso4cPP55CdW4ivjyf97uyMj7cHnh6uDOrbjUcfGoanhxsZp/J475Pv2bB1D1ar7TrclWguZAZLCCGuo+BAPyb/6X6mz5zH8dQsPv/frzwxfgTOWqfG7poQQjRZW3YnYzSasFit9v2sahUmYM223bRr3QK1StWgek6mZzNz9iKqawxEhgfxp0eG43aBM1JbRoeyYOlGdu1N4ddlmzhw+CSJ/bqx58hJcgqKUClB4+ZF21YtUCgU1/huxa1GAiwhhLjOAv19mPz4/Xwycx6p6dnM+GYBT4wfQXllNbUGIyEBvmhl6aAQoomxWq2cyMwhM6cAd1cd8bFRuLnobkjbaVl5mExmKssqMdXaZ/6ddE64ebhSVFJOUAOW8e07eIzZv6zEbLaQ0KYF4x8YfNFl2i46Zx66/y7ax7fkp1/Xkpqezeff/IqrpyvObs4oFApWbN6FvqqGXp0Srum9XkxxmZ7NSQfJyi/Ew9WFHp3iaRkRekPavhq1BiPVBiNWq7XZZ8+VAEsIIW4Afz9vJj9+P9NnzSM9M5c33v8a7wBvVGoVVquVAbd3pHNCq8buphCiGThzRl9ZVc1FH4ZNZjPfL15LYUk5JrMZtUrFpqSDPHhPX8KDA657/4zVBsryy7DZbCgUCvtrNUZKaoxM/+oXbu8cT7fO8fj72g8ILiwpZ1fyEcr0lUSGBlFdXsWyNduw2aBnt3aMGta3QQ/9CW1iiI4M4cMv5lJYWEplWSWGGgNu3m4AbNtziO7t4tCor+8jdHGZnq/nr8BktmCz2dBXVrNg9RYG3tGJjrfFXte2r5TRZGLpxp0cz8gGbCSdyGHQHZ1IiI3+3XXnFZWQV1SCh5srUSGB1yRwM5nNnMorRKVUEhbkj+o6BIMSYAkhxA3i5+vFpMfu5+2PvqO2xkBhThFeAV4oVUrW7dxLoJ83YUH+jd1NIcQtLKewmHmrNmE0mrFYrRxIX8C9A3oSHRpUp9zu5GMUFJdhttgf8E1mMwqFggVrtjL54Xuv2zK5svIKfvp1LRnpOQA4OTvh5u2GDRumaiNmg4mKympWb9zF6o27iIkKJTo6lEMZmdhs9lm3Q4dTqSq3p10feldPBvTuckX9dXXR4ennicFqoaK0ApPBRGleKWonNe6erhSX6hs0g/Z7bE46gMlswWKxYDKYUKlU2Gw21u3cR7vWMahUdYOCWoORwyczqKyuITTQjxZhwb/7c1RVU0tS8jEy8wrw8XCja0IcAacD2nMtWr+d1KxcLFZ7FkaLwcjyLbvwcHMl4iqDcYvFwi+rNpOZVwCAUqFA56zlkWEDcb/AEs+GOpJ2iiUbdpweGxtKpZLRiXde85+9EmAJIcQNZDCb8Qn2pSinCLPJTGl+KS4eLlhdtCQlH5MASwhx3RhNJuYsXY/BdDbZjrnWwM/LN3Bv/57U1hooLaugpEzP3uTjVFfXYrFYsFltKFVKtDotZoOZnPwiQs/7XmUwGklJzURfWU2wvw8x4SFXNNtgs9n4bc9hFizbSG2tERedlg7tW5Oam49SqcBitdIqOpyRA3uSnVvEjqRk9icf52R6NifTs1EoFDi7OmO1WjFUGwBo174VA+/selVj5e3pRnllFRqthqryKgzVBsxGM6WF5Xw44ye6dWzDHV0TCA70A+wzTntSjlNeUUlUSBBtW7W46NJvi8VCdkERoCA00K/eDEqtwcjho+mUlertKeVP59tQKBRotBrmL91A65YRRIYF4+nhSm5hCT8uW4fVasNssaBRqwnw8WLsPf1Qqxu2V+18+soqvv51lWMfXE5BMSlppxg5oCcx4SEAmM1mTuUWcvhoGiajGcvp2TatTotN58T2fYevOsDaeeAImbkFmM85R9JktrBo/XYeGjqgXvnM3AJ2JR+hoqqGFmHBdElojYuztk6ZsopKFq/fXqdOgJ9WbGDyQ/fipKn7+corKmHDrgOU6fV0bXllSzMlwBJCiBuo1mDAyUmNV4AXZQVljjNYKkoq2FdlINzfl4Q2MY4fzDabjVN5hRzPzMZJoyY+JgofT/dGvgshxM3oWHoWVpsNq9VKVVkVxhqj46H405nzLnmt1WKlptJ+OO/7038kJiqUNq2iaNMqEpVaxQ/L1tkTUpjtD/jeHm48NHRAvYdWm83GicxsDhxLxWaD+JZRBPl4MXfhOlKOpQMQH9eCB0YMwNPDFZPZTElZBS46rWPmIiYqlJioUEYN7cvWXQdZsX4nJoOJmsoawB6IeAZ4UmO++qytvTq3JSu/CDPg7uOOm5cbJoMRm9GCXl/Fpu372LR9H9ERwbSMCedw5ilsp+8vI6eAXclH+eO9d6E77yE/PTuPX9dtxWazOfo6ckAvAn29OXQklX0Hj5NyPB2z+WwQoHZSY7VYsVqsGGuNbN15gK07DwDg7emOGSuolGi0GjROGkxmM/nFpSQdOsbt7dtc1f1v3pNM7en9VGajGbPJHkB9M2cZAV6eFJfqKddXYLtAssWaihoUSgWmSgOpt7UiKjwYpfLsbFqNwUBaVh4KhYIW4cFoNfUD0d3Jx6gor8RYY8R0OrW+WqOmqqyKpLAUwkIC8PPxRK1Ws+/ICdbu2OsInIpKyzlwLJVHR96Ni84Zo8lMUXEZm3ftR19agclowmKyl1VpVDhpnVi+fift28Tg5+OFq4szeUWlfL90LWazBWenKw+XJMASQogbKCTAD4vFikqtwjvIG0O1gdrqWky1JspKK/hu7gqcNGoS2sTQsV0rTubkkZqdi8lsQalQ8NvBoyT26Ezba7C2XQjRvNQYjNRW11J6+pc7ZygUCtzcdIQHB+Dt5YG3tzv6ympS0jKxKkCpVGI2mjHWGrEYzRhqDRxPPcXx1FMsWrEZjUaN2lmD1kWLVueEyWymuFzP9v0p9OnSrk4fVmzZRUpqhmNv0eEjqZQXV2AxW3DRablvaF86t49zLG/TqNUE+nlf8H6cnbXc0bUtu4+dxFBrpKayBrPRjJuPGxonDdrfka01MiSQ4f16sGprEjW1BmxKG13btWXgHZ3IzS9m+65kkvYfIS0zl7TMXBRKBTo3HTo3Z8wqJSaTiU1JBxhwe0dUKhUKhYLqmlrmr9mM6fTYW61WDFUGZnyzAFOtyREgKBQQHORHtcmIWqtBdXoWSoGNAC8vgry9yMjKIyMrn9Lyijr9VijsZ3y5erqSfCLtqgOstKw8TEYTFcUVGGoMdd6rKKsEQKlU4O3lTlVtLUqVCpXGvoyxtqoWi8lCaXE5H30xF28vdzq3j6Nz+9YUlutZvX0PCoUCBWC12RjR7w5ahAWTmZVPyrF0Uo6nk5mVX69PZqOZ2qpaZv+80nGvvt4eVBoMqNRK1Bo1SpUSs8lCqdnCBzPmYDaZKSuvvOh9mgwmaitrWb8xifUbkwDQap1QqZVYbDb7PbleeWIXCbCEEOIGctY60bdbOzbuOoDJDDo3He6ebrjptLSJDGf/oROkZ+ay58BR9hw4ilKpROuqReemw0nnhNVmY9W23cRGhEqqdyFEg1ksVjLScyjKKQZArVHj7uuOWqPGyUnDqMTetAg7e4iv1WrFtmYLqadysdpsaJ00eHi68fCwAbg4azl6IpOUY+kcPpZOVVUNJpOZmoqzM0hKlZLlWcUcOZSKq4sOV1dnAA4cT8OmsD+cV5VVYagxAhATHcb4Bwbj6eF6Rffl4qwlPDiAzNx81OfMNGjUKroltP5dY9YmJoK4FuHUGowkHzxI165dAAgLCWD0iP4MH9ybLTsPsHLDDoy1Jqr11VTrqx3XL08vYPnyrfalfWoVCqUCs8UKCvsYmU1mx/I/gBZRoXRIiKV9fEs8PdzYfeg463fuw2azYbVZiYuO4J4+3RwJNqxWK8fTspizZB21Nf/f3p1HR1Xejx9/z5rJLJlksoeQDQhL2BdlESmLtLJIFRBx/brW1mqPba16WuvxtD1Vv9af1vq12lq1lqqtFgXFDSsKuCAB2QlLEhKy78vsM/f5/REcjRDWTELC53WO5zgz9948z4fcyf3c5z6fx9+RpB2pvOht92I5Mm/rVOdiBYMhWhtbqa9uANXRVnOsGaPJiMlkZPF3LyQ9NZGEeAcGg4FPv9zNxq07I4mjPd6GToO8tDR27S2mqbmNtR99wdqPvsBkNmGxW4i1x4IO/F4/f/vnm6iQhvcbiZxer8MYY8JsMWO2mFFKEQqGMOsNpLoSqK1rpKGplfqv/jRkAAAgAElEQVTGli774cZz5Fh6El1O7LZY6ppb0Bn0GEwdSWs4GEZpGpkpybS3ualvbMHnD8A3ckpdMHyswx+XJFhCCNHDzhs9nNQkF5t37sPr8zM0dyBjhg3CbDIy84IJNDS1sHX7PtZ9spX2dg/eNi/eNi+mGBMJaQmYTUZKK2sYljuwt7sihOgD6hqa+ce/3+FQeTUA9ng71jgrOn3Hhf+AlKSjilzo9XoWz72Q6rpGymvqsMfGMiR7QGROz/jRQxk/eihtHi9PvPAaHrcPv8dP0B9EKUU4FCYcCkce++uKTq/DmRjHmLH5p5xcfWXRrKn865111De1oNfpCWlhxgwdxKj8Mx/p1x0prvDNR9y+EmM2cf6EEWw9cBCf14+nzUvAG0AprePROdUxGhUOawSCoWMe32wxEWuPZcaUscyaPL7TZxMKhjB2WB4t7R6slpijbqrp9Xry8waSnpFM45GRLL/XT1tDG6FgiEPFlTz9wutcOn8GqSdZlGPP/lJeW72O+oZmACw2Cw6XA4PRgF6vJy8zjVEjBnXaZ8rYESQ4HXz65W6aWloZkp3J9AmjiI+zoy2cSfGhCgq37aXwy70EAkGCjUHaGtuO+tmJLifDh3Q8dpqZkcI/13yI2+slGApjNBjQ63VcOX826Uf6EgyGKCmv5JW3PsTvDxIOhtDCGgaTEaPJQEZaEku+O4OE+DgMBj1KKV59bz2HKqsjyaDJYWT00DzmTp0AdDzi6fH6+Nurb1Pf2EI4FMZikkcEhRCiT8jOSCU7I/WYnyUmOJkzYxIBvWLLrn342nx42jwE/UHqD9eTkpl8VAUpIYT4NqUUn23exco1HxEIBIl32rnysrkE0di2t5iW1hamjh/NyPzcLkc50pJdx62Y57DGkpGeTG1DEyrBjlIKpSl06BiRl8WgzHTaPV7cbh8l5VUUl1cSCoXRwhpGkwGHy4E5xnTUXKVTYbXE8D/f/y61jc20uT2kJib02Hpddmss6ckuKmobMMV8PZfIZDRw0ZQJjMrPIxzWCIVClFXWsvKD9QSDHY9H6g16DEYDRqOBEYNzjnl8g8Fw3Hm3Op2O78+exj/f/G9HyX2bDps9FqMGNZUN7N1/iIf++A9mTB3Hd2eeh8USg6Ypahub0Ol0pLji0el0NLe0sXLNx2zbuR+A1BQXuYMyKa+rx2gwEA5rpCW5WDBj8jHbMSx3IMNyB1JYWMiECRMi7+v1OgbnZjI4N5OU9CQ+3rQNb7sXn9sHQIwlBovdwncmj+U754/t9Ht405KL2VNcxuHqOhLiHIwemoct1vJ1jE1G8vOyyM0ZQFVdA9o3JoSZjAbmXngeSd+oeqjT6Vh80QXsLSln14FSDHo9Y4YN6jRyq9PpsFljuWj6JN766DOCMgdLCCH6l9FDctlTUobJbMIWb6OpuomAL0BNWS0tTW2Q1dstFEKcLarqGtm0q4im1nYGpCQyMi+Lt977hJ17igEYNzqfpZfMwnrkArVgcA6FhYWMGTboeIc9KZfMnMqKN9dGyoobTAZSE+OZ953JnarY+fwB/u/lNyKjB1/RoWN43pl/oaW44klxHV1GPNoWzZrGK29/SEu7p2PEStMYOTg3sg6UwaDHYDAzOGcAQ/OyOFhe+fUIitHIkOwBpCWdftn3FFc8t115CftKDx8p057MgJRE3B4vb773CZ8X7uTDDYUUfrmHaVPGcKCmhnBYQwFmo4H0uHg++Xw7gUAQs8nId2dNZsbUcRiNBtxeH3WNzThsVhLj484oTvm5mWwtOoDFZulU5MNo0DN2xJCjknyT0cjo/DxG5+cd97iXzbmA19aup7ahGb1ej6ZpTJ8wqlPi9BW9Xs+IQdmMGJR93GMOyx2Ix+fjoy+2YzyNdbIkwRJCiLNUZloy5xUM5fOdezEaDKRmpdBY04i7xcM//vUODQ0tzJ15XtTWoxFC9A37yypYs+GLSJGEispa3nl7Y8fjTRYzSy+ZxYQxw6L2811OBz9cdgn7yypodXtIT3IxMC35qO8mS4yZJXMv5D9rN0QusKEjQeupEadosFtjueGyi6mqb6Td7SUt2UXcMdZq0ul0XDJzKkWl5ezYVwI6GDUkj6E5mWfcBpPRSMG3RsHsNitXXDqHqZNG8dqbH3KovJq33/8Us8VMfGo8SlM01TRRFDgIwJiCwXx/3gwS4r8eMbPFWrB96/HR05WRnMjwvCz2FJdFEkyjoWOuXEKc/bSPa421cM3Ci2hqbcPt9ZPich5VvfJ0jB8+hLFDB9Hc0kZJ8YFT2lcSLCGEOItNnzCKUfm5lFRUYzYaGTQwg0+/2Mmqdz7m7Q8+paaukSsuuwjzaTwjLoQ4u1XXN/Lh5m3UNDRjNpsYP2wQ5xUM6zQfSCnFB5u+JBjqKKXd3thO+5Eqb/EJDu64cSmuhDMbeTgZRqPhpEahstJTuf2qSzlcXYdSisy0ZIyG01ur6Wyi0+nISE6EEyxlqNPpGJabxbDcnnsEISszlZ/csozX1qzj0007CPgC1B6qjXxuNBuZPWMSF3/n/Ki2Q6fT8b1pkxiRl82e4jL0ej0Fg7MZkJLULcdPiHOQENe9y5jo9XpsVsuJN/wW+YsshBBnuXiHnXHDBkdez7xgPClJ8fz9lbfZsr2IhqYWbrxqIXGO05sgLoQ4+zS2tPGvtesj6yH5/AE27dxHm9vLuCF5VNc2UFXbwOHKWooPHCLgD3aqSOdMdpKcntQjydWpMuj1Xc5BFdGh1+tIH5BMWm4arQ2ttDe1gw7iXHE4k+JISu6ZRyt1Ot1x5yD3F5JgCSFEH1QwLI+f/GAZf3nxDQ6VV/PoUy9zzbLv0ehup6axmaR4J6MG5XSaECyE6Ds+37mX8JHFZd0tbvy+jgp9JbtKeUt9fMx9DEYDJosJZ5ITs8WMLfb0C0eI/mdgWjIxMSbiU+KxJ9jR6XQYjAYMBgOZqScYehOnRBIsIYToozLSkvjpD5fztxWrKSmr4k9/fZXUrGQs9lhKKqrZsnc/yy6aQaLz7LuDLYQ4vur6JlobWmmpb0ELa50+s9tiGZCeTFpKImkpiZRU11Dd3PzNASyMRgMTR+T3bKPFWS0rLYWM5CQqausj75mMBnIz0kg/gyIb4miSYAkhRB/msFv50Q2LeeTpl6ipaqC6tJaE1HjikuIIaxr//eJLls65sLebKYQ4SZqm+HLnPvbtOBhZeNUca8bmtGGKMWGJjeGHSxd0Kms+MTSMtzZsorSyBsORKmoThw2h4ASV0sS5RafTcdnsaew6eIidB0rR6XSMHpLL8B6cD3aukARLCCH6OJPJiC3JQbwWprmmmaaaZjRNkZAaT2VdA5qmjrlIphCidyilaGxtR1MaiXFxkfNz38EyVr+zgfLKjgIEphgTzmQnsfbYSDnroTkDj1ozymQ08v3vTKXd46XN48UV5yDGfOZV1ET/Y9DrGT0kl9FDznwRZtE1SbCEEKIfMBoNxCc7MZmN1JXX01LXQkysGUe8HaniLsTZo765lTc3bsLj86PTgdFgZMLgXDZ9sYu9+w8BEOewcfHsyWQOTGVd4Q7qmlowm4yMyc9j2pgRXR7bbo3t0+XOhegvJMESQoh+oCA3m+0HSrA5bQQDIZprmqk/XM/wQdmyTpYQZ4lQOMx/1m3EFwgCEAwEaapqYtemPUDHOlGzL5zIjKnjMB8Zgbpm/myUUnIeC9GHSIIlhBD9wLQxBdS3tFJV30hSmougL4C7xUPRrmL8F54vjwsJcRYoqawhrCmUUjRVN9Fc19xRWl0Hw4bmcvVlc7Hbjh6BkuRKiL5FEiwhhOgHjEYDi2ddQF1TCw0trdimx/Diy29TXdvIyyvf59rLLz7tizSlFF5/AKNBj9kkiZoQp8vj8xMMBKkqqcLX7gPAnmAnITWB4SPzjplcCSH6HkmwhBCiH0lOcJKc4ATghqsW8v+eeomt2/eRnZnGd6aNP+XjVdY38t/CbbR7fSgUmclJzJk4htgYWV9HiFNlUFBWVE4oEMJgNJCSnUKsPRaT0cDAFFmHSIj+Qt/bDRBCCBEdaSkuli+eC8Cqd9ZzsOTwKe3f6vaweuMmWtwewpqGpikO19azasMmlFInPoAQImLrjn38/Z9vEQqEiLHGMGDIAGLtsRgMehKdceSkp/Z2E4UQ3UQSLCGE6MfGjhzCrOkT0DTF8y+voaW1/aT33VF8CE3TCIfCNFQ20N7UjqYUze1uaptaothqIfoPTdNY/e4GXnh5DYFgiIljh3PV5d8jMy2Z5HgnU0cN57LvTJWlFIToR+QRQSGE6OfmXzSN8ooa9hcf5rmX3uLHNy7BaDSccL/G1jYaqhtprGpEC2sAJA1IIiUzmTaPl1RXfLSbLkSf5vH6ePFf77BnXyl6vY5FF1/IhVPGRhZ4FUL0TzKCJYQQ/ZzBoOfaZfOId9opLavi9TUfH3d7pRQ79xTzxYZt1B+uRwtrxFg75lzVV9RTfaiaJKejJ5ouRJ/h9vn4omg/7xd+yY6SQ5RX1vL/nnqZPftKsVkt3Po/lzFj6jipCCjEOUBGsIQQ4hzgsFu5fvkC/viXf7Ph821kD0xj/JihaEphMnw9mlVZXcfraz5m38FyAGIsZhIzk7DGWWlraqOmtIbG6ibefv9TLl80G4NB7tMJUdvcwupPNhFWCk3T2LH7IIf3V6CFNTLSkrjxqoUkupy93UwhRA+RBEsIIc4R2QPTWLzgO/zrjQ946T/v8+n+/VhsFhLsNiYOymPT5l18tnkXSimssTF8d9Zkxo3Jp7DoICVVNTgH2hg5KIePPyrk88JdeDw+rl12MSaT/CkR57YPt24nGA6jlKKhooH6w/UADBiYwh03LJV16IQ4x8hfRSGEOIdMmTSS9YU7qDpcS/necrJHZrP/cD2fflCIFtbQ63VcMHks35t1PjZrx5o8M8ePZuY3jjEyL5tn/v4GO/Yc5M8vrOSmqy8h1iJl28W5yRcIUFPXREtdC60NrQT9QQCSByaTlJMiyZUQ56AeT7CUUtxzzz3k5+dz4403Eg6HefDBB1m/fj3hcJgbbriB5cuXA1BaWsovf/lLmpqasFqtPPTQQwwaNKinmyyEEP1Gc7ubhIGJNDW14nP7OLDlABypuJ6ekcz/XH4xqcmu4x4jNzuDO25ZylPPreRgSQVP/vVVfvA/38dht/VAD4ToOa0eD5uLDlDZ0ESM2cTo3GzyMzPQ6XQ0NrWyZUcRhV/upaqmIbKP0WwkLTcNe4Idk1HuYwtxLurRM//gwYM88MADbN++nfz8fABefvllSktLefPNN3G73SxbtoyCggJGjx7Nz3/+c6677joWLlzIRx99xE9+8hNWr14tE0SFEOI0tXg8GI1GModmUrK9hHAoTExsDCk5KQwbnH3C5Oor6alJ/OQHl/PUcys5XFXH48/8mx9efylGs4nmdjfxditOmyRcou9q9/pYueFzgqEQCvAGAny8bSebt+yhoaaR4kOVkW2NJiP2BDtxSXHEOmLR6XQY9HqGZw/svQ4IIXpNjyZYK1asYOnSpWRkZETeW7t2LZdffjlGoxGn08n8+fNZtWoVqampFBcXM3/+fABmzJjBAw88wO7duykoKOjJZgshRL/hctjRNA1TjInskdn4PX4cLgdGg4GU+FObhJ+Y4OQntyzl6edf53BVHQ//aQXZBTnYHLFomiLdlcCc8aMxGk5cEl6Is8324lJC4TBhTaO1oZWWuhbam9sjI74mk5GRw/OYMHoY2dlprNm0hXaPF0XH0zoDk5MYO0hKsQtxLurRBOvXv/41ABs3boy8V1VVRXp6euR1WloaRUVFVFVVkZKSgl7/dYWq1NRUqqurJcESQojTFGe1kp2awqGaWmJiY4iJjUEHGA16CnKzTvl4DruN225awqNPv0JdbSMHvjxATkEO1jgrVY1NbCo6wNQRQ7u/I0JEWVl1HdVlNTRVNREKhiLvx7kczJg8lgsmjiImxhx5//IZ06huaqbN4yXJ6cDlkKUMhDhX9frDwUqpTo/8KaXQ6/VomnbUo4BKKQyneCd0586d3dLOvqqwsLC3m9AnSJxOnsTq5J2tsYpXCp81hlqPD00p4sxmMuNs7DmD78vUIWn4QkHaGtso2VlCTkEONqeNvWXlxHjbj7vv2Rqns5HE6uScTJwCYQ2FwqzXd7reaG51s+dAJcVlNWhax3BVjDUGV5qLuKQ4TCYjVlOYnTt3dHnstpoqSs68Gz1CfqdOnsTq5EiczoIEKz09ndra2sjr2tpa0tLSyMjIoK6urlMC9tVnp2LkyJHExJyb1a0KCwuZMGFCbzfjrCdxOnkSq5N3rsXqy3c+IGt4FhX7K2iubaZ8bzmDxw3GZDYyfvz4LufO9qc4Nba1s720lKZ2N4kOB2Nys7t1Hlp/ilU0nShOrR4P/922kxaPBx0QYzYxY+QImupaWLdxC0UHyiLbOlwOXOkubE4bOp0OvV7HgMREpkwa1wM9iT75nTp5EquT0x/j5Pf7T3nAptcTrNmzZ/Paa68xc+ZMPB4Pb731Fg888ABpaWlkZWWxZs0a5s+fz/r169Hr9ZHiGEIIIc4eaQnxVDU2MWDIAAK+AJ5WD+X7ypl8wdhzojBRdVMz7235krCmoYBmt4fS2lrmTZxAUpw8Kna20DSNt77YgjcQ6Hgd1qg5XMdjH+/A5/EBYDYZOW/8CC6cOg5vOMiGnXvwB0MoFDmpKVw4akRvdkEI0Qf0eoK1fPlyysrKWLRoEcFgkGXLlnHeeecB8Oijj3Lffffx1FNPYTabefzxxzvNyRJCCHF2mDpiKKs++4KwpjFw6EAObD2Au9mN1urv7ab1iE/3FhHSNMKhMH6PH4vNgjLo+bxoH/Mn9a+7uX3Z4YbGjsIVoTB15XU0VDQQDoUBsFotzJo+gSkTR2GzWiL7ZKUk4/H7MRuNUnZdCHFSeuWb4sEHH/y6AUYjv/zlL4+5XU5ODi+++GJPNUsIIcRpSnDYWTJ9KrsPlVHf0kZ6XBzrPviCdesLGTk0l0E5A3q7iafN7fNT3dyM2Wggw+XC8K0bfa1tbg7uL6elvoX2xvaO+cJGA/Ep8fjSvaiJ6pwYxesLWtrdVJZUU1tWG0msYh2xJGUmcf64EVxQMPyofXQ6HTaL5aj3hRCiK3IrRgghRLewWWKYNHRI5LUhqPjg4838/ZW3uevHV2G3xfZi607P1uISdpWXo9Pp0dFxsT137Gj0Ydi++wA7dh/kYGkFSqnIPqYYE0F/kIbKBhoqG3io/EXOGz+CCWOG44yzoZTiUF09eysqCYXDZCcnMywzA5OUs4+aYDDExk3beX/dJtxHHgW0OW2k5qZic9owGY1kJJ7cGnBCCHEikmAJIYSIinlzplBcWkFJWRX/fPVdbrpmEXp93xnJqWpsYnf5YcKaAsL43D6aa5t59NPduFvcke30ej1p6UkYHTHYXQ5MMSa87V6aa5ppq2uhuraRVe9s4M33NjJsSA6utAR8ZtCO7N/icVNSW8P8CeOPGh0TJ6/d52NvRSVlHh/mQ2UMyUjHqNPzeeEu3lu3iZbWjmqW8a44krKSiXVaIwsCO2ItZKck93IPhBD9hSRYQgghosJgMHDtsnn8759WsHtfKes2bmHW9L4zH6mosopAKERTdRO1ZbX42n2Rz0wmIyPycxg1YjAjhuZgiTGzYfdeSmpq0et1GOJsjBs2mElDBlG0/xCbtuxm594SdheVQFEJBqMBV7qLxAGJWB1W2r0+SmtrGXSKlXJFh7rWVt7/cjuaUmhKsa3kEOs++5LGsjqamtsAyEhLYv5FUxk2JJt9lVXsPVxBWNPIS0tlVHaWJLdCiG4jCZYQQoioSYh3cOXiufz1H6t4872N5GVnkJOVfuIde5nX56do10EOFJUR9AcBMBgNOJOdJKYlMP+C88lJS+m0z4UjRzApfzDtXh+O2FgsZhMAI4cPYuTwQbS7Pby3YTObt+7F0+ahrryOusN15I3OIz4lnoqGJkmwTtMne/cR0jSUUjTVNFF1sAq/p6PASmqyi4vnTGH0iMGREdThAzMZPjCzN5sshOjHJMESQggRVSOH5/GdaeNZt3ELL7yyhrt+fBXW2N4tGuAPhjjcUE8wrJGRkECctWN+WEurm48+2cInm3bg83eU8rbYLaRmp5KQmoBO3/FI2YCkxGMeN9ZsJtZsPuZndpuVKeeNwmc10NrcRu2hWhqrGinZXsLgcYOIzey7hUB6UyAUosXjobmumaoDVXjbvQCYY81kDhnAj5culArEQogeJQmWEEKco3ZVHKbJ7T7xht0gaXAqSwZfDMCW8kNff+Cws2FfUY+0oSv17rZOr115KSzIm33cfT4vPnDaPy8rNQlSk2Bobqf3/Vro+LE4C2J1tsrLSIWMVBgz9KjPPjmwv0fbkmCzUTBARseEOJfJLR0hhBBCCCGE6CYygiWEEOeo3rjLvm3XAZ7755vo9TpGTivAEmcl1elkYm4uTqv1jI7d5Hazs7ycZo+HeJuNkZmZJNhsnbYpKq/gg01baa5vobWxLVK4QqfXkTsok+ULZpGclHBG7TgZSilaPV5CWpg4Syz/+Pc7bNt1ALstlttvXkpq8tElwwsLC5kwoe8UCekOFU1NbDp4EH+wYx7cAJeLLLuT9z74nF1FJQDEWmKYMXUcAYeRNp8PpWno9HoyE11MHz68T1WuFEL0D5JgCSGE6DFjCgaTmz+Qkn3lFBXup+CCAmpaWnhvxw4WjBvX5fylE6ltbeXD3bsJax3Fz9t8Piqbmjg/O5fm+hYOlBzmQMlhqmsbO+1nMBpIyUomNTuVwZkZPZJcQcd6Wk7b1wnlNZd/D/8/VrN3/yGeeu4/3H7zUhITnD3SlrNVk9vNhqKiyL+pt93Lui37aajs+Dc0m03MmDKWmdMnROb0Nba3s23nLiaOGY0jtu+tuyaE6B8kwRJCCNFjWjweUganU1PdgKfVw8GtB0nLS8PhtLO/uprRWVmdtm/zetlSWkpNaytGvZ68lBRGDRx4VEntzcXFhMIda1V5Wj20NbTR2tjKp+2fddrOZDISG2fF4bLjcDmwOW3o9XqMej05yb23DpLRaOSGKxfw5+dXUnyokqf+9h9uv/lynHG2E+/cT+2u6Cij7mn1UF1STf3heqBjtHHKpJFcPGsKDnvnUU+X3U6cySjJlRCiV0mCJYQQose0er0YjAYGjx/Mzg07aalroaWuBYBd1l1syspgQEYymekpJCfHs6HkIKEjIxiBcJh91dW0eDyMTs+kqqaeqpoGqmrq2V1chrfdi9JUp5+n1+sZnJvZ8V9eJlkDUjnc2Mhn+/ejjqyZZNTryUxMZICrZ0avumI2m7j52kU8+exrHK6s5c/P/4cf37QEm/XcSxY0TePAgXIO7C2lreFIERIdJGcmkz1sIDPGjTkquRJCiLOFJFhCCCF6TFxsLEopLDYLwycPp66sDnerG2+bF6/Hx869xezcWxzZ3mgyYnVascXZCIfCeNo8eNu8rAyFj3l8s8VMrCMWh8uBw+XAleRk6eTJnbbJSUkmKc5BaW0dwXCYAS4XyXEOdLren6sTa4nh1v+5lCf+8m+qahp4+vnXufKK79Hi99GqaQRCIczGM//T3eLxUFpfT0jTGJCQQGpc3DH77wsE2F1ZSXVLC2aDgfz0dAa6XGccqzafj/KGBsJaR5n8RLsdALfHx+eFO1n/2bbIAsF6g56kzCTSctOw2CzodTriz3C+nhBCRJMkWEIIIXqM02ol2eGgtrUVm9OGbVTHI3BGvZ7zs3Kpr2uioqqOiqo6SsqrCPiDtNa30lrf2uk4sbExZKYnk5aaRHpKIm5C1Prd6AxfPzpo0OsZnnnsQh52i4WRWQOj19EzYLfF8sPrL+OPf/kXZRU1PPXCSkZMGYFBr+etL7/kgvx8kuPijrlvIBTCGwhgjYnBZDAcc5sD1dVsP3w4MrfpUH096U4nkwcP7pQ4+YNB3tu1i0AwiALcwOaSElo8HkYNPP3YFdfW8uWhQ2hKoYD9NTXE6Uw0lNWxedtegsEQAK6EOJwDXCRkuDCaOi5XDHo9Q1JTiTGZTvvnCyFEtEmCJYQQokddOGwYWw8dori2lrCmkRIXx8S8POKtVrIzUpkwZhgAW0tL2VlaRnuLG0+rB71BjzXOit1pY8GE8Z2qDmpKUVhczMHaWgx6PZqmMSglhYIBfXPx3ninncsum83fV7xFS30rezftZdh5w1DAJ/v3s3DcuE6L52qaxtZDhyhraECv06EpxeDUVEZmZnZKmnzBINvKy9GUQgtrBANBlKY42ObFjpEEm41QOEw4rHGwuoaa+nrCYQ2UIsYagzXOyr7qavLT0o5KcgKhEGX19bT6fLhsNjJdLozfSvL8wSBbv0qulKKxupGq4ipavpFADx2cxYVTxjE8PwdPwM+2sjKqW1qIMRoZlp7OoNTU6ARdCCG6iSRYQgghepTRYGBSXh6T8vLYvHkzE0eOPOZ2Q9PTOVhbi8liJiG1Y36UXqcjyeE4qqS7Xqdj0qBBjMnOxu33Y4uJ6ZZH6XpTc9BHwZQR7Ni4k6aaZja/V4jFGoPFasF7uJkBqUm44h0kxMdR2d7K4ebGjsRJdcxDO1BTQygQwmkwU9/UQkNjC+VVdRyurcfn9hHwBTr9vM0UnrBNOr0Oe7wdb3kTw/IGkpWZRpIrnna/j4/27EHTNMJKUd7QwJ6KCmYWFGAxmfD7A1TW1LNjfykHSspob3bjbnWjhTtG0fQGPUOGZnPZ3OmdStTbLRam5ed3Y1SFECL6+vZfHyGEEH3a8ebyWGNimF1QwOaSEhra29HrdOQkJTE+J6fLfcxGY59PrL6iKYU1zkrBlBHs/mwPQX+QoD9IW1M7dRX1R21vMBqwWGMwxZjwewP4PD4++lbRj2/S6XQYzUb0Bj06nQ6L2YTdYkFv0GM0GGgP+AmEw3V4+9YAABD5SURBVOj0OnTo8LZ78bZ7aWtsY3PjbjYX7gY65o3Z4+1Y4mKJS7ATa4/F2+7D3epmzxdFeNu81Dc2o47RFIvNQnpuGilZKQzLHHDM9b+EEKKv6R9/hYQQQvRLCTYbF40ciaZp6HS6s6IQRU/JSU6mvr0de7ydSXMnEvAF8Hn9hHxBcp0umlvbaGpuo7GplfqmFsKhMO5WT6djmGJMZKQkkpjgJNHlJN5pp6ihFlOsmRhLDLoji/Aa9HpmDh/eaWHmJrebD/fsiczVAggHQ+ALkWiwUHa4hkOHq2ltc+Ot9kN1130xGPSkJrtIT02kKRwgNi4WW5wNU4wp8vNzkpK6MXpCCNF7+m2CpY7cKgsEAifYsn/z+/293YQ+QeJ08iRWJ09idXIkTseWYrOR5nBQ19aGhobZGoPDHsuE7Oyjilx8tGcPrW4Pfl+AUCCEOcZETGwMSXEOzh88uNO2ue0D2FxSAoACUIohKSlYjcZO/xZWo5EJmZnsqKggrBQohSshnrHZ2Z1GCZtb23lnUyHtzW7aW9z4vH4s1hisdiuOeBszx44mOdGJ4ch8rOrmZr4sL+/Y+cjf6kHJyUf9/DMhv1MnT2J18iRWJ6e/xemrXEIdaxi+Czp1Klv3IW1tbezbt6+3myGEEEIIIYTo4/Lz83E4HCe1bb9NsDRNw+12YzKZzqlHSoQQQgghhBDdQylFMBjEZrN1qt56PP02wRJCCCGEEEKInnZyaZgQQgghhBBCiBOSBEsIIYQQQgghuokkWEIIIYQQQgjRTSTBEkIIIYQQQohuIgmWEEIIIYQQQnQTSbCEEEIIIYQQoptIgiWEEEIIIYQQ3UQSLCGEEEIIIYToJpJg9QHr1q1j4cKFfPe73+WOO+6gvb098llVVRXTp0+nsbGxy/1LS0u56qqrmDdvHkuWLOHgwYMAPPPMMyxatCjy3/Tp0xk/fnzU+xMtZxqnr7z66qvceuutx/zs+eefZ8GCBd3W5t5yprHavn07V1xxBYsWLWLhwoW88cYbnT5XSnH33Xfz7LPPRq0PPSWasXr//fdZuHAhixYt4tprr6WsrCyqfYmmY8XJ5/Nx7733smDBAubPn8+9996Lz+c75v6NjY3cdNNNzJs3jwULFrBly5ajtlm7di3jxo2Ldlei7kxj9ZUNGzawaNGio97v7+dfd8VKzr+vHTp0iOuvv55FixYxb948/va3v0U+e/HFF5k2bVrkWuHKK6/sqW5FxbFi1dbWxh133MGCBQuYN28ezzzzTJf7d3VNpZTiscceY968ecybN4+7774br9fbU92KijON1VeOdV316quvMm/ePObOncv9999PMBiMVjd6hxJntYaGBjV58mRVUlKilFLq4YcfVvfff79SSqmVK1eqmTNnqvz8fNXQ0NDlMRYvXqxWrVqllFJq3bp1av78+UrTtE7btLS0qLlz56p169ZFpR/R1h1xampqUvfdd58aO3asuuWWW476fPPmzWratGlq/vz50ehCjznTWGmapmbMmKE2btyolFKqqqqq0/EOHDigrrnmGjVmzBj117/+Ndrdiapoxsrr9aoxY8ao0tJSpZRSzz33nLr55puj3qdo6CpOjz76qLrrrrtUOBxWoVBI3Xnnneqxxx475jHuuOMO9dRTTymllNq9e7e64IILlMfjiXxeUlKi5syZo8aOHRv1/kRTd8TK6/WqRx99VE2cOPGo76Nz4fzrjljJ+dfZFVdcof71r38ppZRqbW1Vc+fOVZ988olSSqk777wzcg3R13UVq9/85jfqt7/9rVJKKbfbrWbOnKm2bNlyzGN0dU317rvvqsWLFyu/3680TVO33367+vOf/9wj/YqG7ohVV9dVRUVF6sILL1QNDQ0qHA6rO++8Uz3zzDNR71NPkhGss9yGDRsYNWoUOTk5ACxfvpzVq1dTU1PD2rVrT3iHsqamhuLiYubPnw/AjBkz8Hg87N69u9N2Dz30ENOnT2fGjBlR6Ue0nWmcAN5++21SUlK4++67j/qsvr6e3/zmN/ziF7/o7qb3uDONVSAQ4LbbbmPq1KkApKWl4XK5qK6uBmDFihUsXbqU733ve1HtR0+IZqzC4TBKKdra2gBwu93ExMREtT/R0lWcJk6cyA9/+EP0ej0Gg4Hhw4dTWVl51P6hUIh169Zx+eWXAzB8+HBycnJYv349AF6vl7vuuot77rmnx/oULWcaq6+O4fV6efDBB4/67Fw4/7ojVnL+dbZkyZLI0xkOh4OsrKzItlu3bmX16tUsXLiQG2+8kaKioh7pVzR0Fatf/vKXkb/9dXV1BAIBHA7HUfsf75pq7ty5vPTSS5jNZtxuN42NjcTHx/dY37rbmcYKur6u+uCDD5g1axYulwu9Xs+yZctYtWpVVPvT04y93QBxfNXV1aSlpUVep6Wl0d7ejs1m409/+tMJ96+qqiIlJQW9/utcOjU1lerqagoKCgA4cOAAa9euZe3atd3fgR5ypnGCji8PgP/85z+d3g+Hw/zsZz/jrrvuwmjs+6fMmcYqJiaGpUuXRl6/8soruN1uxo4dC8Cvf/1rADZu3NjNLe950YyVxWLhgQce4IorriA+Ph5N03jppZei0o9o6ypO48aNw263A1BRUcELL7zAb37zm6P2b2pqQtM0XC5X5L2vvqeg43dq2bJlDB06NMo9ib4zjRXAnDlzmDNnDp9//vlRn50L5193xMpms8n59w2LFy+O/P/HH3/M1q1b+d3vfofH4yEvL4+bb76ZSZMmsWbNGm6++WbefvttbDZbdDsWBV3Fyu12Y7fb+fnPf867777LRRddRG5u7lH7n+iaymQy8Y9//IPHHnuM1NRULrrooh7pVzScaayg6+uqqqoqMjMzOx27pqYmCr3oPTKCdZbTNA2dTnfU+988uU91f6UUBoMh8vqFF17g6quv7vIORF9wpnE6nj/84Q9MmjSJadOmnfGxzgbdGatnnnmGJ554gj//+c9YLJbuaN5ZJZqxKioq4sknn2TNmjVs2LCBW2+9ldtvvx2lVHc0vUedKE47d+7kqquu4uqrr2bmzJkntf9X31MrVqzAaDSyZMmS6DS+h51prM4l0YyVnH/H9vrrr3PXXXfxxz/+kZSUFKxWK88++yyTJk0CYN68eTidTnbs2NH9HekBJ4rVI488wmeffUZLSwtPPvnkSe3/7Wuqq6++mi+++II5c+Zwxx13dHMPes6Zxup4vn2eKaW65XrtbNK/etMPpaenU1tbG3ldU1OD0+nEarUec/sPPvggMhH15ptvJiMjg7q6uk6/zLW1tZG7EuFwmPfee49LL700uh2JsjON0/GsWrWK9957j0WLFvGrX/2KsrKyY04s7yu6I1aBQICf/vSnvPnmm7z88ssMGzasR9re06IZqw0bNjB+/HiysrIAuOqqq9i/fz9NTU1R7lX3O16c3nrrLW644QZ+9rOfRSY579ixo1OBncTERJRSNDc3R45RW1tLamoqK1eujGx/yy234PP5WLRoUZ+923mmsTqXRDNWcv51jpNSigcffJDHH3+c559/PvJYc0VFBS+++GKnn6eU6rNPc3QVq8LCwsh3is1mY/78+ezevfuUrqn27t0bmX6h0+lYunQpu3bt6tkOdqMzjdWpHPub16X9Rm9M/BInr76+Xk2ZMiUyyfCRRx5R99xzT6dtTlS84dJLL1VvvvmmUkqpjz/+WM2ePVuFw2GlVMdk8jlz5kSn8T2oO+L0lddee+2YRS6UUuqzzz7r80UuuiNWt99+u7r55puV2+3ucpu77767z0+yj2asPvnkEzVz5kxVV1enlFLqnXfe6bPnYldx+uCDD9TkyZPV9u3bT3iMH//4x+rpp59WSim1Z88eNWXKFNXa2tppm/Ly8j5f5KI7YvWV430f9efzrztiJedfZw8++KC67LLLjvoua2hoUOPHj1fbtm1TSnUUdZg1a5by+/3d3o+e0FWs7r33XnXfffcpTdOU3+9XN910k3ruueeOeYyurqlWrlypLrnkkkhxnieeeELdeuutPdGtqOiOWH3l29dVe/bsUTNnzlT19fVK0zT105/+VD3xxBNR7E3P65u3IM4hiYmJ/P73v+eOO+4gGAySlZXFQw89dErHePTRR7nvvvt46qmnMJvNPP7445Gh2NLSUgYMGBCNpveo7ojTueJMY7V161beffddcnJyIs9XA/z85z9n+vTp0Whyr4l2rG688UauueYaTCYTTqeT//u//4tGN6KuqzgtW7YMpRS/+tWvItuOHz+e+++//6hj3H///fzqV79iwYIF6HQ6Hn744T792HJXuiNW54poxmrKlCly/h1RXV3N888/T3p6Otdff33k/WuvvZbFixfz2GOP8etf/5pgMIjdbufJJ5/EbDb3WP+6U1ex0uv13H///SxcuBDomLt37bXXHvMYXV1Tff/736esrIzFixdjMBgYMmQIv/vd73qye92qO2LVlWHDhnHbbbdx3XXXEQwGGTNmzAlHvfoanVJ98IFjIYQQQgghhDgLyRwsIYQQQgghhOgmkmAJIYQQQgghRDeRBEsIIYQQQgghuokkWEIIIYQQQgjRTSTBEkIIIYQQQohuImXahRBC9AuzZs2ioqIC6FjoMzY2lqFDh3Lbbbed9BICn332GS6Xi/z8/Gg2VQghRD8mI1hCCCH6jXvuuYcNGzbw0Ucf8corrzB+/Hh+8IMf8Mknn5zU/tdddx319fVRbqUQQoj+TEawhBBC9Bt2u53k5GQAUlNT+cUvfkFdXR2///3vWb16dS+3TgghxLlARrCEEEL0a8uWLWPfvn0cOnSIgwcPctNNNzFu3DhGjRrF8uXL2b9/P9DxiCHA9ddfzxNPPAHA5s2bWbJkCaNHj2b+/Pm8/vrrvdYPIYQQfYMkWEIIIfq1QYMGAbB//35+9KMfkZGRwRtvvMHLL7+Mpmk8/PDDALz66qsAPPbYY9xwww3U1dVxyy23sHDhQlavXs1tt93Gb3/7W/773//2Wl+EEEKc/eQRQSGEEP2aw+EAwOPxsGTJEq688kpsNhsAl156KU8//TQALpcLAKfTic1m4y9/+Qvnn38+1113HQDZ2dkUFxfzwgsvREa7hBBCiG+TBEsIIUS/1t7eDnTMz5o9ezZvvPEGO3fupLi4mN27dxMfH3/M/YqLi1m/fj3jxo2LvBcKhSKJmBBCCHEskmAJIYTo14qKigAYMGAAS5Yswel0MmfOHBYsWEBxcTHPPPPMMfcLhULMnz+fH/3oR53e1+vl6XohhBBdkwRLCCFEv/baa69RUFBAZWUl1dXVrFq1CpPJBMCGDRtQSh1zv9zcXDZv3kx2dnbkvRUrVlBbW8udd97ZI20XQgjR98htOCGEEP1Ge3s7dXV11NbWUlRUxO9+9zvWrFnDPffcQ3x8PF6vl/fff5/Dhw/z73//mxUrVhAIBCL7W61W9u/fT1tbG1deeSV79uzhD3/4A6Wlpbzzzjv87//+L6mpqb3YQyGEEGc7nerq1p0QQgjRh8yaNYuKiorI68TEREaMGMGtt97KxIkTAfjTn/7EihUr8Pv95Ofnc/nll3Pvvffy4YcfkpGRweOPP86zzz7L8uXLuffee/n000955JFHKCoqIjk5mauvvpobb7yxt7oohBCiD5AESwghhBBCCCG6iTwiKIQQQgghhBDdRBIsIYQQQgghhOgmkmAJIYQQQgghRDeRBEsIIYQQQgghuokkWEIIIYQQQgjRTSTBEkIIIYQQQohuIgmWEEIIIYQQQnQTSbCEEEIIIYQQopv8f7n5sectjGjOAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# national migration index\n",
    "figure_index(data_Index, fs = 14, subject = 'China')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# provincial migration index (move in)\n",
    "figure_index(data_Index, fs = 14, subject = 'Hubei (move in)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# provincial migration index (move out)\n",
    "figure_index(data_Index, fs = 14, subject = 'Hubei (move out)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# From the above conclusion: method 1 🌚 method 2 🌝 \n",
    "# method 1\n",
    "# Get the travel size ratio: n2p\n",
    "# examples:\n",
    "# 01月01日， 全国热门迁入地（目的地）是：广东省，迁入人口数量占全国迁入人口总量的13.67% \n",
    "# 2020-01-01\tmove_in\t广东省\tGuangdong\t13.67\n",
    "# 01月01日， 全国热门迁出地（出发地）是：广东省，迁出人口数量占全国迁出人口总量的14.98%\n",
    "# 2020-01-01\tmove_out\t广东省\tGuangdong\t14.98\n",
    "#data_N2P = load_N2P_raw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last update:  2020-03-10\n",
      "Data date range:  2020-01-01 to 2020-03-10\n",
      "Number of rows in raw data:  121712\n"
     ]
    }
   ],
   "source": [
    "# method 2\n",
    "# Get the travel size ratio: p2p\n",
    "# 01月01日，迁入新疆人口主要来源地为：甘肃省，占新疆迁入人口总量的 14.89%\n",
    "data_P2P = load_P2P_raw()\n",
    "# the index of province A move in province B (from B to A) should be equal (at least close to) \n",
    "# that of province B move out province A (from B to A)\n",
    "# examples proving the above statement\n",
    "#temp_in = data_P2P[(data_P2P.direction == 'move_in') & (data_P2P.province_name == '新疆维吾尔自治区') & (data_P2P.province_name_io == '甘肃省')]\n",
    "#temp_out = data_P2P[(data_P2P.direction == 'move_out') & (data_P2P.province_name == '甘肃省') & (data_P2P.province_name_io == '新疆维吾尔自治区')]\n",
    "#[(x+y)/2 for x,y in zip(*[temp_in, temp_out])][:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>direction</th>\n",
       "      <th>province_name_io</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>value</th>\n",
       "      <th>ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>52982</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.086661</td>\n",
       "      <td>23.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52983</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>河南省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.055776</td>\n",
       "      <td>15.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52984</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广东省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.053276</td>\n",
       "      <td>14.49</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52985</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>重庆市</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.051658</td>\n",
       "      <td>14.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52986</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>安徽省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.020480</td>\n",
       "      <td>5.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52987</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>江西省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.020259</td>\n",
       "      <td>5.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52988</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>陕西省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.016178</td>\n",
       "      <td>4.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52989</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>四川省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.014450</td>\n",
       "      <td>3.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52990</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>江苏省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.009817</td>\n",
       "      <td>2.67</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52991</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.007464</td>\n",
       "      <td>2.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52992</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>上海市</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.004375</td>\n",
       "      <td>1.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52993</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>北京市</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.003934</td>\n",
       "      <td>1.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52994</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>福建省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.003677</td>\n",
       "      <td>1.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52995</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>河北省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.002831</td>\n",
       "      <td>0.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52996</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>山东省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.002537</td>\n",
       "      <td>0.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52997</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.002280</td>\n",
       "      <td>0.62</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52998</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>贵州省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.002059</td>\n",
       "      <td>0.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52999</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>云南省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.001360</td>\n",
       "      <td>0.37</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53000</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>天津市</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.001287</td>\n",
       "      <td>0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53001</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>山西省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.001287</td>\n",
       "      <td>0.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53002</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>甘肃省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.001066</td>\n",
       "      <td>0.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53003</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.001029</td>\n",
       "      <td>0.28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53004</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.000662</td>\n",
       "      <td>0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53005</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>青海省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.000552</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53006</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>海南省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.000478</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53007</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>辽宁省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.000441</td>\n",
       "      <td>0.12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53008</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53009</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.000404</td>\n",
       "      <td>0.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53010</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>move_out</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.000368</td>\n",
       "      <td>0.10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      update_date direction province_name_io province_name province_name_en  \\\n",
       "52982  2020-01-31  move_out              湖南省           湖北省            Hubei   \n",
       "52983  2020-01-31  move_out              河南省           湖北省            Hubei   \n",
       "52984  2020-01-31  move_out              广东省           湖北省            Hubei   \n",
       "52985  2020-01-31  move_out              重庆市           湖北省            Hubei   \n",
       "52986  2020-01-31  move_out              安徽省           湖北省            Hubei   \n",
       "52987  2020-01-31  move_out              江西省           湖北省            Hubei   \n",
       "52988  2020-01-31  move_out              陕西省           湖北省            Hubei   \n",
       "52989  2020-01-31  move_out              四川省           湖北省            Hubei   \n",
       "52990  2020-01-31  move_out              江苏省           湖北省            Hubei   \n",
       "52991  2020-01-31  move_out              浙江省           湖北省            Hubei   \n",
       "52992  2020-01-31  move_out              上海市           湖北省            Hubei   \n",
       "52993  2020-01-31  move_out              北京市           湖北省            Hubei   \n",
       "52994  2020-01-31  move_out              福建省           湖北省            Hubei   \n",
       "52995  2020-01-31  move_out              河北省           湖北省            Hubei   \n",
       "52996  2020-01-31  move_out              山东省           湖北省            Hubei   \n",
       "52997  2020-01-31  move_out          广西壮族自治区           湖北省            Hubei   \n",
       "52998  2020-01-31  move_out              贵州省           湖北省            Hubei   \n",
       "52999  2020-01-31  move_out              云南省           湖北省            Hubei   \n",
       "53000  2020-01-31  move_out              天津市           湖北省            Hubei   \n",
       "53001  2020-01-31  move_out              山西省           湖北省            Hubei   \n",
       "53002  2020-01-31  move_out              甘肃省           湖北省            Hubei   \n",
       "53003  2020-01-31  move_out              吉林省           湖北省            Hubei   \n",
       "53004  2020-01-31  move_out         新疆维吾尔自治区           湖北省            Hubei   \n",
       "53005  2020-01-31  move_out              青海省           湖北省            Hubei   \n",
       "53006  2020-01-31  move_out              海南省           湖北省            Hubei   \n",
       "53007  2020-01-31  move_out              辽宁省           湖北省            Hubei   \n",
       "53008  2020-01-31  move_out             黑龙江省           湖北省            Hubei   \n",
       "53009  2020-01-31  move_out           内蒙古自治区           湖北省            Hubei   \n",
       "53010  2020-01-31  move_out          宁夏回族自治区           湖北省            Hubei   \n",
       "\n",
       "          value  ratio  \n",
       "52982  0.086661  23.57  \n",
       "52983  0.055776  15.17  \n",
       "52984  0.053276  14.49  \n",
       "52985  0.051658  14.05  \n",
       "52986  0.020480   5.57  \n",
       "52987  0.020259   5.51  \n",
       "52988  0.016178   4.40  \n",
       "52989  0.014450   3.93  \n",
       "52990  0.009817   2.67  \n",
       "52991  0.007464   2.03  \n",
       "52992  0.004375   1.19  \n",
       "52993  0.003934   1.07  \n",
       "52994  0.003677   1.00  \n",
       "52995  0.002831   0.77  \n",
       "52996  0.002537   0.69  \n",
       "52997  0.002280   0.62  \n",
       "52998  0.002059   0.56  \n",
       "52999  0.001360   0.37  \n",
       "53000  0.001287   0.35  \n",
       "53001  0.001287   0.35  \n",
       "53002  0.001066   0.29  \n",
       "53003  0.001029   0.28  \n",
       "53004  0.000662   0.18  \n",
       "53005  0.000552   0.15  \n",
       "53006  0.000478   0.13  \n",
       "53007  0.000441   0.12  \n",
       "53008  0.000404   0.11  \n",
       "53009  0.000404   0.11  \n",
       "53010  0.000368   0.10  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_slice = data_P2P[(data_P2P['update_date'] == datetime.date(int(2020),int(1),int(31)))]\n",
    "data_slice = data_slice[(data_slice['province_name_en'] == 'Hubei')]\n",
    "data_slice = data_slice[data_slice['direction'] == 'move_out']\n",
    "data_slice.sort_values(by = 'ratio', ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "error_list = consistency_P2P(data_P2P)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>direction</th>\n",
       "      <th>province_name_io</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>value</th>\n",
       "      <th>ratio</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>33640</th>\n",
       "      <td>2020-01-20</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>14.978473</td>\n",
       "      <td>84.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33727</th>\n",
       "      <td>2020-01-20</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>14.976127</td>\n",
       "      <td>25.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31987</th>\n",
       "      <td>2020-01-19</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>14.775449</td>\n",
       "      <td>26.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31900</th>\n",
       "      <td>2020-01-19</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>14.774792</td>\n",
       "      <td>84.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35380</th>\n",
       "      <td>2020-01-21</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>14.148596</td>\n",
       "      <td>81.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35467</th>\n",
       "      <td>2020-01-21</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>14.144053</td>\n",
       "      <td>23.76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35496</th>\n",
       "      <td>2020-01-21</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>13.502102</td>\n",
       "      <td>59.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35468</th>\n",
       "      <td>2020-01-21</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>13.501142</td>\n",
       "      <td>22.68</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33756</th>\n",
       "      <td>2020-01-20</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>13.157203</td>\n",
       "      <td>61.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33728</th>\n",
       "      <td>2020-01-20</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>13.155180</td>\n",
       "      <td>22.54</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30131</th>\n",
       "      <td>2020-01-18</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>12.728727</td>\n",
       "      <td>83.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30218</th>\n",
       "      <td>2020-01-18</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>12.726771</td>\n",
       "      <td>23.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28420</th>\n",
       "      <td>2020-01-17</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>12.664592</td>\n",
       "      <td>83.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28507</th>\n",
       "      <td>2020-01-17</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>12.661421</td>\n",
       "      <td>24.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30247</th>\n",
       "      <td>2020-01-18</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>11.961889</td>\n",
       "      <td>59.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30219</th>\n",
       "      <td>2020-01-18</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>11.961536</td>\n",
       "      <td>22.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31988</th>\n",
       "      <td>2020-01-19</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>11.656250</td>\n",
       "      <td>20.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32016</th>\n",
       "      <td>2020-01-19</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>11.655015</td>\n",
       "      <td>59.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28508</th>\n",
       "      <td>2020-01-17</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>10.932552</td>\n",
       "      <td>21.50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28536</th>\n",
       "      <td>2020-01-17</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>10.932232</td>\n",
       "      <td>58.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26680</th>\n",
       "      <td>2020-01-16</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>10.361309</td>\n",
       "      <td>81.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26767</th>\n",
       "      <td>2020-01-16</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>10.357934</td>\n",
       "      <td>23.27</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37120</th>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>9.953458</td>\n",
       "      <td>77.77</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37207</th>\n",
       "      <td>2020-01-22</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>9.950370</td>\n",
       "      <td>23.81</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35989</th>\n",
       "      <td>2020-01-21</td>\n",
       "      <td>move_out</td>\n",
       "      <td>安徽省</td>\n",
       "      <td>江苏省</td>\n",
       "      <td>Jiangsu</td>\n",
       "      <td>9.946008</td>\n",
       "      <td>34.63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35844</th>\n",
       "      <td>2020-01-21</td>\n",
       "      <td>move_in</td>\n",
       "      <td>江苏省</td>\n",
       "      <td>安徽省</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>9.940891</td>\n",
       "      <td>34.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26796</th>\n",
       "      <td>2020-01-16</td>\n",
       "      <td>move_in</td>\n",
       "      <td>广东省</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>9.552628</td>\n",
       "      <td>57.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26768</th>\n",
       "      <td>2020-01-16</td>\n",
       "      <td>move_out</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>9.552267</td>\n",
       "      <td>21.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39991</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>move_out</td>\n",
       "      <td>河北省</td>\n",
       "      <td>北京市</td>\n",
       "      <td>Beijing</td>\n",
       "      <td>9.532309</td>\n",
       "      <td>39.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39846</th>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>move_in</td>\n",
       "      <td>北京市</td>\n",
       "      <td>河北省</td>\n",
       "      <td>Hebei</td>\n",
       "      <td>9.527424</td>\n",
       "      <td>54.16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69219</th>\n",
       "      <td>2020-02-09</td>\n",
       "      <td>move_in</td>\n",
       "      <td>青海省</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>Jilin</td>\n",
       "      <td>0.000031</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77915</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>move_in</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>Jilin</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78465</th>\n",
       "      <td>2020-02-15</td>\n",
       "      <td>move_out</td>\n",
       "      <td>贵州省</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74437</th>\n",
       "      <td>2020-02-12</td>\n",
       "      <td>move_in</td>\n",
       "      <td>青海省</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>Jilin</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74438</th>\n",
       "      <td>2020-02-12</td>\n",
       "      <td>move_in</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>Jilin</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76175</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>move_in</td>\n",
       "      <td>青海省</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>Jilin</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76176</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>move_in</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>Jilin</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76669</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>move_out</td>\n",
       "      <td>海南省</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76668</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>move_out</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73249</th>\n",
       "      <td>2020-02-12</td>\n",
       "      <td>move_out</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74929</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>move_out</td>\n",
       "      <td>江西省</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74931</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>move_out</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74930</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>move_out</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68002</th>\n",
       "      <td>2020-02-09</td>\n",
       "      <td>move_in</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73191</th>\n",
       "      <td>2020-02-12</td>\n",
       "      <td>move_out</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>0.000028</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68031</th>\n",
       "      <td>2020-02-09</td>\n",
       "      <td>move_out</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78408</th>\n",
       "      <td>2020-02-15</td>\n",
       "      <td>move_out</td>\n",
       "      <td>贵州省</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>0.000027</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83674</th>\n",
       "      <td>2020-02-18</td>\n",
       "      <td>move_out</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83675</th>\n",
       "      <td>2020-02-18</td>\n",
       "      <td>move_out</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76727</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>move_out</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76726</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>move_out</td>\n",
       "      <td>江西省</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77104</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>move_in</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>海南省</td>\n",
       "      <td>Hainan</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76117</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>move_in</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76118</th>\n",
       "      <td>2020-02-13</td>\n",
       "      <td>move_in</td>\n",
       "      <td>青海省</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86536</th>\n",
       "      <td>2020-02-19</td>\n",
       "      <td>move_in</td>\n",
       "      <td>甘肃省</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77857</th>\n",
       "      <td>2020-02-14</td>\n",
       "      <td>move_in</td>\n",
       "      <td>青海省</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90010</th>\n",
       "      <td>2020-02-21</td>\n",
       "      <td>move_in</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88823</th>\n",
       "      <td>2020-02-21</td>\n",
       "      <td>move_out</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107979</th>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>move_out</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.000020</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68408</th>\n",
       "      <td>2020-02-09</td>\n",
       "      <td>move_in</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>海南省</td>\n",
       "      <td>Hainan</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>121712 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       update_date direction province_name_io province_name province_name_en  \\\n",
       "33640   2020-01-20   move_in              广东省       广西壮族自治区          Guangxi   \n",
       "33727   2020-01-20  move_out          广西壮族自治区           广东省        Guangdong   \n",
       "31987   2020-01-19  move_out          广西壮族自治区           广东省        Guangdong   \n",
       "31900   2020-01-19   move_in              广东省       广西壮族自治区          Guangxi   \n",
       "35380   2020-01-21   move_in              广东省       广西壮族自治区          Guangxi   \n",
       "35467   2020-01-21  move_out          广西壮族自治区           广东省        Guangdong   \n",
       "35496   2020-01-21   move_in              广东省           湖南省            Hunan   \n",
       "35468   2020-01-21  move_out              湖南省           广东省        Guangdong   \n",
       "33756   2020-01-20   move_in              广东省           湖南省            Hunan   \n",
       "33728   2020-01-20  move_out              湖南省           广东省        Guangdong   \n",
       "30131   2020-01-18   move_in              广东省       广西壮族自治区          Guangxi   \n",
       "30218   2020-01-18  move_out          广西壮族自治区           广东省        Guangdong   \n",
       "28420   2020-01-17   move_in              广东省       广西壮族自治区          Guangxi   \n",
       "28507   2020-01-17  move_out          广西壮族自治区           广东省        Guangdong   \n",
       "30247   2020-01-18   move_in              广东省           湖南省            Hunan   \n",
       "30219   2020-01-18  move_out              湖南省           广东省        Guangdong   \n",
       "31988   2020-01-19  move_out              湖南省           广东省        Guangdong   \n",
       "32016   2020-01-19   move_in              广东省           湖南省            Hunan   \n",
       "28508   2020-01-17  move_out              湖南省           广东省        Guangdong   \n",
       "28536   2020-01-17   move_in              广东省           湖南省            Hunan   \n",
       "26680   2020-01-16   move_in              广东省       广西壮族自治区          Guangxi   \n",
       "26767   2020-01-16  move_out          广西壮族自治区           广东省        Guangdong   \n",
       "37120   2020-01-22   move_in              广东省       广西壮族自治区          Guangxi   \n",
       "37207   2020-01-22  move_out          广西壮族自治区           广东省        Guangdong   \n",
       "35989   2020-01-21  move_out              安徽省           江苏省          Jiangsu   \n",
       "35844   2020-01-21   move_in              江苏省           安徽省            Anhui   \n",
       "26796   2020-01-16   move_in              广东省           湖南省            Hunan   \n",
       "26768   2020-01-16  move_out              湖南省           广东省        Guangdong   \n",
       "39991   2020-01-23  move_out              河北省           北京市          Beijing   \n",
       "39846   2020-01-23   move_in              北京市           河北省            Hebei   \n",
       "...            ...       ...              ...           ...              ...   \n",
       "69219   2020-02-09   move_in              青海省           吉林省            Jilin   \n",
       "77915   2020-02-14   move_in          宁夏回族自治区           吉林省            Jilin   \n",
       "78465   2020-02-15  move_out              贵州省           青海省          Qinghai   \n",
       "74437   2020-02-12   move_in              青海省           吉林省            Jilin   \n",
       "74438   2020-02-12   move_in          宁夏回族自治区           吉林省            Jilin   \n",
       "76175   2020-02-13   move_in              青海省           吉林省            Jilin   \n",
       "76176   2020-02-13   move_in          宁夏回族自治区           吉林省            Jilin   \n",
       "76669   2020-02-14  move_out              海南省       宁夏回族自治区          Ningxia   \n",
       "76668   2020-02-14  move_out              吉林省       宁夏回族自治区          Ningxia   \n",
       "73249   2020-02-12  move_out              吉林省           青海省          Qinghai   \n",
       "74929   2020-02-13  move_out              江西省       宁夏回族自治区          Ningxia   \n",
       "74931   2020-02-13  move_out              吉林省       宁夏回族自治区          Ningxia   \n",
       "74930   2020-02-13  move_out             黑龙江省       宁夏回族自治区          Ningxia   \n",
       "68002   2020-02-09   move_in              湖北省           青海省          Qinghai   \n",
       "73191   2020-02-12  move_out              吉林省       宁夏回族自治区          Ningxia   \n",
       "68031   2020-02-09  move_out              吉林省           青海省          Qinghai   \n",
       "78408   2020-02-15  move_out              贵州省       宁夏回族自治区          Ningxia   \n",
       "83674   2020-02-18  move_out              吉林省           青海省          Qinghai   \n",
       "83675   2020-02-18  move_out          广西壮族自治区           青海省          Qinghai   \n",
       "76727   2020-02-14  move_out             黑龙江省           青海省          Qinghai   \n",
       "76726   2020-02-14  move_out              江西省           青海省          Qinghai   \n",
       "77104   2020-02-14   move_in          宁夏回族自治区           海南省           Hainan   \n",
       "76117   2020-02-13   move_in          宁夏回族自治区          黑龙江省     Heilongjiang   \n",
       "76118   2020-02-13   move_in              青海省          黑龙江省     Heilongjiang   \n",
       "86536   2020-02-19   move_in              甘肃省          黑龙江省     Heilongjiang   \n",
       "77857   2020-02-14   move_in              青海省          黑龙江省     Heilongjiang   \n",
       "90010   2020-02-21   move_in          宁夏回族自治区          黑龙江省     Heilongjiang   \n",
       "88823   2020-02-21  move_out             黑龙江省       宁夏回族自治区          Ningxia   \n",
       "107979  2020-03-03  move_out              吉林省           青海省          Qinghai   \n",
       "68408   2020-02-09   move_in          宁夏回族自治区           海南省           Hainan   \n",
       "\n",
       "            value  ratio  \n",
       "33640   14.978473  84.39  \n",
       "33727   14.976127  25.66  \n",
       "31987   14.775449  26.29  \n",
       "31900   14.774792  84.70  \n",
       "35380   14.148596  81.30  \n",
       "35467   14.144053  23.76  \n",
       "35496   13.502102  59.60  \n",
       "35468   13.501142  22.68  \n",
       "33756   13.157203  61.46  \n",
       "33728   13.155180  22.54  \n",
       "30131   12.728727  83.51  \n",
       "30218   12.726771  23.45  \n",
       "28420   12.664592  83.29  \n",
       "28507   12.661421  24.90  \n",
       "30247   11.961889  59.30  \n",
       "30219   11.961536  22.04  \n",
       "31988   11.656250  20.74  \n",
       "32016   11.655015  59.18  \n",
       "28508   10.932552  21.50  \n",
       "28536   10.932232  58.11  \n",
       "26680   10.361309  81.25  \n",
       "26767   10.357934  23.27  \n",
       "37120    9.953458  77.77  \n",
       "37207    9.950370  23.81  \n",
       "35989    9.946008  34.63  \n",
       "35844    9.940891  34.58  \n",
       "26796    9.552628  57.84  \n",
       "26768    9.552267  21.46  \n",
       "39991    9.532309  39.86  \n",
       "39846    9.527424  54.16  \n",
       "...           ...    ...  \n",
       "69219    0.000031   0.01  \n",
       "77915    0.000030   0.01  \n",
       "78465    0.000030   0.04  \n",
       "74437    0.000030   0.01  \n",
       "74438    0.000030   0.01  \n",
       "76175    0.000030   0.01  \n",
       "76176    0.000030   0.01  \n",
       "76669    0.000030   0.02  \n",
       "76668    0.000030   0.02  \n",
       "73249    0.000029   0.04  \n",
       "74929    0.000029   0.02  \n",
       "74931    0.000029   0.02  \n",
       "74930    0.000029   0.02  \n",
       "68002    0.000028   0.02  \n",
       "73191    0.000028   0.02  \n",
       "68031    0.000027   0.03  \n",
       "78408    0.000027   0.02  \n",
       "83674    0.000026   0.03  \n",
       "83675    0.000026   0.03  \n",
       "76727    0.000025   0.03  \n",
       "76726    0.000025   0.03  \n",
       "77104    0.000024   0.02  \n",
       "76117    0.000024   0.01  \n",
       "76118    0.000024   0.01  \n",
       "86536    0.000022   0.01  \n",
       "77857    0.000021   0.01  \n",
       "90010    0.000021   0.01  \n",
       "88823    0.000021   0.01  \n",
       "107979   0.000020   0.01  \n",
       "68408    0.000018   0.01  \n",
       "\n",
       "[121712 rows x 7 columns]"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_P2P.sort_values(by = 'value', ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_network_P2P = network_P2P(data_P2P)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>source</th>\n",
       "      <th>source_en</th>\n",
       "      <th>target</th>\n",
       "      <th>target_en</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26630</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>安徽省</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>0.140842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26625</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>北京市</td>\n",
       "      <td>Beijing</td>\n",
       "      <td>0.061303</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26647</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>重庆市</td>\n",
       "      <td>Chongqing</td>\n",
       "      <td>0.027764</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26644</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>福建省</td>\n",
       "      <td>Fujian</td>\n",
       "      <td>0.102513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26643</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>甘肃省</td>\n",
       "      <td>Gansu</td>\n",
       "      <td>0.018305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26633</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>0.153650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26634</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>0.032048</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26645</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>贵州省</td>\n",
       "      <td>Guizhou</td>\n",
       "      <td>0.061247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26640</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>海南省</td>\n",
       "      <td>Hainan</td>\n",
       "      <td>0.008641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26638</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>河北省</td>\n",
       "      <td>Hebei</td>\n",
       "      <td>0.025765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26650</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>0.019407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26639</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>河南省</td>\n",
       "      <td>Henan</td>\n",
       "      <td>0.075540</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26641</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>0.008212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26642</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>0.054876</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26624</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>Inner Mongolia</td>\n",
       "      <td>0.006302</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26636</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>江苏省</td>\n",
       "      <td>Jiangsu</td>\n",
       "      <td>0.296323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26637</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>江西省</td>\n",
       "      <td>Jiangxi</td>\n",
       "      <td>0.099085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26626</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>Jilin</td>\n",
       "      <td>0.016021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26646</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>辽宁省</td>\n",
       "      <td>Liaoning</td>\n",
       "      <td>0.018877</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26629</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>0.004760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26649</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>0.003801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26648</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>陕西省</td>\n",
       "      <td>Shaanxi</td>\n",
       "      <td>0.031547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26631</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>山东省</td>\n",
       "      <td>Shandong</td>\n",
       "      <td>0.058320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26622</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>上海市</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>0.433362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26632</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>山西省</td>\n",
       "      <td>Shanxi</td>\n",
       "      <td>0.013923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26627</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>四川省</td>\n",
       "      <td>Sichuan</td>\n",
       "      <td>0.057937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26628</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>天津市</td>\n",
       "      <td>Tianjin</td>\n",
       "      <td>0.015387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26635</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>Xinjiang</td>\n",
       "      <td>0.006502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26623</th>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>云南省</td>\n",
       "      <td>Yunnan</td>\n",
       "      <td>0.040584</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      update_date source source_en    target       target_en     value\n",
       "26630  2020-01-31    浙江省  Zhejiang       安徽省           Anhui  0.140842\n",
       "26625  2020-01-31    浙江省  Zhejiang       北京市         Beijing  0.061303\n",
       "26647  2020-01-31    浙江省  Zhejiang       重庆市       Chongqing  0.027764\n",
       "26644  2020-01-31    浙江省  Zhejiang       福建省          Fujian  0.102513\n",
       "26643  2020-01-31    浙江省  Zhejiang       甘肃省           Gansu  0.018305\n",
       "26633  2020-01-31    浙江省  Zhejiang       广东省       Guangdong  0.153650\n",
       "26634  2020-01-31    浙江省  Zhejiang   广西壮族自治区         Guangxi  0.032048\n",
       "26645  2020-01-31    浙江省  Zhejiang       贵州省         Guizhou  0.061247\n",
       "26640  2020-01-31    浙江省  Zhejiang       海南省          Hainan  0.008641\n",
       "26638  2020-01-31    浙江省  Zhejiang       河北省           Hebei  0.025765\n",
       "26650  2020-01-31    浙江省  Zhejiang      黑龙江省    Heilongjiang  0.019407\n",
       "26639  2020-01-31    浙江省  Zhejiang       河南省           Henan  0.075540\n",
       "26641  2020-01-31    浙江省  Zhejiang       湖北省           Hubei  0.008212\n",
       "26642  2020-01-31    浙江省  Zhejiang       湖南省           Hunan  0.054876\n",
       "26624  2020-01-31    浙江省  Zhejiang    内蒙古自治区  Inner Mongolia  0.006302\n",
       "26636  2020-01-31    浙江省  Zhejiang       江苏省         Jiangsu  0.296323\n",
       "26637  2020-01-31    浙江省  Zhejiang       江西省         Jiangxi  0.099085\n",
       "26626  2020-01-31    浙江省  Zhejiang       吉林省           Jilin  0.016021\n",
       "26646  2020-01-31    浙江省  Zhejiang       辽宁省        Liaoning  0.018877\n",
       "26629  2020-01-31    浙江省  Zhejiang   宁夏回族自治区         Ningxia  0.004760\n",
       "26649  2020-01-31    浙江省  Zhejiang       青海省         Qinghai  0.003801\n",
       "26648  2020-01-31    浙江省  Zhejiang       陕西省         Shaanxi  0.031547\n",
       "26631  2020-01-31    浙江省  Zhejiang       山东省        Shandong  0.058320\n",
       "26622  2020-01-31    浙江省  Zhejiang       上海市        Shanghai  0.433362\n",
       "26632  2020-01-31    浙江省  Zhejiang       山西省          Shanxi  0.013923\n",
       "26627  2020-01-31    浙江省  Zhejiang       四川省         Sichuan  0.057937\n",
       "26628  2020-01-31    浙江省  Zhejiang       天津市         Tianjin  0.015387\n",
       "26635  2020-01-31    浙江省  Zhejiang  新疆维吾尔自治区        Xinjiang  0.006502\n",
       "26623  2020-01-31    浙江省  Zhejiang       云南省          Yunnan  0.040584"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_slice =  data_network_P2P[data_network_P2P['update_date'] == datetime.date(int(2020),int(1),int(31))]\n",
    "df_slice = df_slice[df_slice['source_en'] == 'Zhejiang']\n",
    "df_slice.sort_values(by = ['source_en', 'target_en'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Chunyun 2020: from January 10 to February 18\n",
    "# the travel size of Chunyun from wikipedia\n",
    "# 14.76 unit = 亿人次 https://zh.wikipedia.org/wiki/%E6%98%A5%E8%BF%90\n",
    "# the travel size of Chunyun from Baidu Qianxi\n",
    "# compare these numbers to deduce the unit of data from Baidu Qianxi\n",
    "# 10603 unit = 十万人次\n",
    "#nation_migration = {\"20200110\":438.973668,\"20200111\":481.0020084,\"20200112\":446.3765172,\"20200113\":436.1630004,\"20200114\":412.6136436,\"20200115\":431.4138732,\"20200116\":450.4974408,\"20200117\":479.9456712,\"20200118\":529.5260304,\"20200119\":525.4227648,\"20200120\":542.3144724,\"20200121\":621.2109996,\"20200122\":580.6973268,\"20200123\":551.6447328,\"20200124\":448.30989,\"20200125\":261.5466672,\"20200126\":287.4244176,\"20200127\":264.7354104,\"20200128\":225.8917632,\"20200129\":192.6017028,\"20200130\":183.7748412,\"20200131\":153.6096312,\"20200201\":130.643928,\"20200202\":142.4592036,\"20200203\":117.190152,\"20200204\":85.9585284,\"20200205\":81.3802464,\"20200206\":81.188244,\"20200207\":85.798116,\"20200208\":94.7500092,\"20200209\":111.1956336,\"20200210\":100.9839312,\"20200211\":74.7511092,\"20200212\":71.3811852,\"20200213\":73.1563812,\"20200214\":73.4141556,\"20200215\":70.6802436,\"20200216\":73.5190992,\"20200217\":92.2017168,\"20200218\":96.6906396}\n",
    "#sum(nation_migration.values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4560.595407920161, 4560.548774240538, 9121.144182160699)"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 9134 unit = 十万人次\n",
    "data_P2P_chunyun = data_P2P[(data_P2P.update_date >= datetime.date(int(2020),int(1),int(10))) & (data_P2P.update_date <= datetime.date(int(2020),int(2),int(18)))]\n",
    "chunyun_in, chunyun_out = sum(data_P2P_chunyun[data_P2P_chunyun.direction == 'move_in'].value), sum(data_P2P_chunyun[data_P2P_chunyun.direction == 'move_out'].value)\n",
    "chunyun_in, chunyun_out, chunyun_in + chunyun_out"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "# What the minimal value would be if we remove 宁夏回族自治区，新疆维吾尔自治区，甘肃省 and 青海省 from the data set\n",
    "#data_P2P_x = data_P2P_x[(data_P2P.province_name_io!='宁夏回族自治区') & (data_P2P.province_name!='宁夏回族自治区')]\n",
    "#data_P2P_x = data_P2P_x[(data_P2P.province_name_io!='新疆维吾尔自治区') & (data_P2P.province_name!='新疆维吾尔自治区')]\n",
    "#data_P2P_x = data_P2P_x[(data_P2P.province_name_io!='甘肃省') & (data_P2P.province_name!='甘肃省')]\n",
    "#data_P2P_x = data_P2P_x[(data_P2P.province_name_io!='青海省') & (data_P2P.province_name!='青海省')]\n",
    "#data_P2P_x.loc[data_P2P_x.value.idxmin()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_if_city, data_if = load_IF_raw()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>city_name</th>\n",
       "      <th>update_date</th>\n",
       "      <th>ratio</th>\n",
       "      <th>province_name</th>\n",
       "      <th>population</th>\n",
       "      <th>value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>12767</th>\n",
       "      <td>武汉市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>0.6906</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>10892900.0</td>\n",
       "      <td>7522636.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40735</th>\n",
       "      <td>黄冈市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.9718</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>6341000.0</td>\n",
       "      <td>12503183.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10943</th>\n",
       "      <td>襄阳市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.6411</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>5654000.0</td>\n",
       "      <td>9278779.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36783</th>\n",
       "      <td>荆州市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>2.0037</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>5641700.0</td>\n",
       "      <td>11304274.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10791</th>\n",
       "      <td>孝感市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.6138</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>4915000.0</td>\n",
       "      <td>7931827.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6839</th>\n",
       "      <td>宜昌市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.6354</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>4135600.0</td>\n",
       "      <td>6763360.24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20671</th>\n",
       "      <td>十堰市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.5553</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>3418000.0</td>\n",
       "      <td>5316015.40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48487</th>\n",
       "      <td>恩施土家族苗族自治州</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>2.6656</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>3361000.0</td>\n",
       "      <td>8959081.60</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36935</th>\n",
       "      <td>荆门市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.7281</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>2901500.0</td>\n",
       "      <td>5014082.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11703</th>\n",
       "      <td>咸宁市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.8751</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>2535100.0</td>\n",
       "      <td>4753566.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40279</th>\n",
       "      <td>黄石市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.8662</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>2470500.0</td>\n",
       "      <td>4610447.10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18999</th>\n",
       "      <td>随州市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.5080</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>2210500.0</td>\n",
       "      <td>3333434.00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11855</th>\n",
       "      <td>仙桃市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.7345</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>1544500.0</td>\n",
       "      <td>2678935.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17023</th>\n",
       "      <td>天门市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>2.0323</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>1283500.0</td>\n",
       "      <td>2608457.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48639</th>\n",
       "      <td>鄂州市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.2986</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>1076900.0</td>\n",
       "      <td>1398462.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20975</th>\n",
       "      <td>神农架林区</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.8703</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>76800.0</td>\n",
       "      <td>143639.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25687</th>\n",
       "      <td>潜江市</td>\n",
       "      <td>2020-01-31</td>\n",
       "      <td>1.4266</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        city_name update_date   ratio province_name  population        value\n",
       "12767         武汉市  2020-01-31  0.6906           湖北省  10892900.0   7522636.74\n",
       "40735         黄冈市  2020-01-31  1.9718           湖北省   6341000.0  12503183.80\n",
       "10943         襄阳市  2020-01-31  1.6411           湖北省   5654000.0   9278779.40\n",
       "36783         荆州市  2020-01-31  2.0037           湖北省   5641700.0  11304274.29\n",
       "10791         孝感市  2020-01-31  1.6138           湖北省   4915000.0   7931827.00\n",
       "6839          宜昌市  2020-01-31  1.6354           湖北省   4135600.0   6763360.24\n",
       "20671         十堰市  2020-01-31  1.5553           湖北省   3418000.0   5316015.40\n",
       "48487  恩施土家族苗族自治州  2020-01-31  2.6656           湖北省   3361000.0   8959081.60\n",
       "36935         荆门市  2020-01-31  1.7281           湖北省   2901500.0   5014082.15\n",
       "11703         咸宁市  2020-01-31  1.8751           湖北省   2535100.0   4753566.01\n",
       "40279         黄石市  2020-01-31  1.8662           湖北省   2470500.0   4610447.10\n",
       "18999         随州市  2020-01-31  1.5080           湖北省   2210500.0   3333434.00\n",
       "11855         仙桃市  2020-01-31  1.7345           湖北省   1544500.0   2678935.25\n",
       "17023         天门市  2020-01-31  2.0323           湖北省   1283500.0   2608457.05\n",
       "48639         鄂州市  2020-01-31  1.2986           湖北省   1076900.0   1398462.34\n",
       "20975       神农架林区  2020-01-31  1.8703           湖北省     76800.0    143639.04\n",
       "25687         潜江市  2020-01-31  1.4266           湖北省         NaN          NaN"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_slice = data_if_city[data_if_city['update_date'] == datetime.date(int(2020),int(1),int(31))]\n",
    "data_slice = data_slice[data_slice['province_name'] == '湖北省']\n",
    "data_slice.sort_values(by = 'population', ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>update_date</th>\n",
       "      <th>province_name</th>\n",
       "      <th>province_name_en</th>\n",
       "      <th>population</th>\n",
       "      <th>value</th>\n",
       "      <th>n_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>安徽省</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>63233400.0</td>\n",
       "      <td>2.907005e+08</td>\n",
       "      <td>4.597262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>北京市</td>\n",
       "      <td>Beijing</td>\n",
       "      <td>21542000.0</td>\n",
       "      <td>8.371006e+07</td>\n",
       "      <td>3.885900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>重庆市</td>\n",
       "      <td>Chongqing</td>\n",
       "      <td>31017900.0</td>\n",
       "      <td>1.236808e+08</td>\n",
       "      <td>3.987400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>福建省</td>\n",
       "      <td>Fujian</td>\n",
       "      <td>39410000.0</td>\n",
       "      <td>1.531519e+08</td>\n",
       "      <td>3.886118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>甘肃省</td>\n",
       "      <td>Gansu</td>\n",
       "      <td>26283200.0</td>\n",
       "      <td>1.045462e+08</td>\n",
       "      <td>3.977683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>112520300.0</td>\n",
       "      <td>4.419054e+08</td>\n",
       "      <td>3.927339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>48849600.0</td>\n",
       "      <td>2.130164e+08</td>\n",
       "      <td>4.360659</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>贵州省</td>\n",
       "      <td>Guizhou</td>\n",
       "      <td>35790100.0</td>\n",
       "      <td>1.458346e+08</td>\n",
       "      <td>4.074720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>海南省</td>\n",
       "      <td>Hainan</td>\n",
       "      <td>3942000.0</td>\n",
       "      <td>1.718801e+07</td>\n",
       "      <td>4.360226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>河北省</td>\n",
       "      <td>Hebei</td>\n",
       "      <td>73910900.0</td>\n",
       "      <td>3.221683e+08</td>\n",
       "      <td>4.358874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>35958300.0</td>\n",
       "      <td>1.516191e+08</td>\n",
       "      <td>4.216526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>河南省</td>\n",
       "      <td>Henan</td>\n",
       "      <td>95383900.0</td>\n",
       "      <td>4.365894e+08</td>\n",
       "      <td>4.577181</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>58458500.0</td>\n",
       "      <td>2.319045e+08</td>\n",
       "      <td>3.966995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>68988200.0</td>\n",
       "      <td>2.879820e+08</td>\n",
       "      <td>4.174366</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>Inner Mongolia</td>\n",
       "      <td>25287000.0</td>\n",
       "      <td>1.250565e+08</td>\n",
       "      <td>4.945486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>江苏省</td>\n",
       "      <td>Jiangsu</td>\n",
       "      <td>80507400.0</td>\n",
       "      <td>3.886402e+08</td>\n",
       "      <td>4.827385</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>江西省</td>\n",
       "      <td>Jiangxi</td>\n",
       "      <td>46196900.0</td>\n",
       "      <td>2.002228e+08</td>\n",
       "      <td>4.334118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>Jilin</td>\n",
       "      <td>26156900.0</td>\n",
       "      <td>1.131208e+08</td>\n",
       "      <td>4.324702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>辽宁省</td>\n",
       "      <td>Liaoning</td>\n",
       "      <td>43955300.0</td>\n",
       "      <td>1.940003e+08</td>\n",
       "      <td>4.413582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>6817700.0</td>\n",
       "      <td>3.286388e+07</td>\n",
       "      <td>4.820376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>5985800.0</td>\n",
       "      <td>2.333910e+07</td>\n",
       "      <td>3.899077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>陕西省</td>\n",
       "      <td>Shaanxi</td>\n",
       "      <td>38065700.0</td>\n",
       "      <td>1.530453e+08</td>\n",
       "      <td>4.020557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>山东省</td>\n",
       "      <td>Shandong</td>\n",
       "      <td>99083400.0</td>\n",
       "      <td>4.561063e+08</td>\n",
       "      <td>4.603257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>上海市</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>24237800.0</td>\n",
       "      <td>1.028604e+08</td>\n",
       "      <td>4.243800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>山西省</td>\n",
       "      <td>Shanxi</td>\n",
       "      <td>37183300.0</td>\n",
       "      <td>1.642341e+08</td>\n",
       "      <td>4.416878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>四川省</td>\n",
       "      <td>Sichuan</td>\n",
       "      <td>83398000.0</td>\n",
       "      <td>3.390837e+08</td>\n",
       "      <td>4.065850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>天津市</td>\n",
       "      <td>Tianjin</td>\n",
       "      <td>15596000.0</td>\n",
       "      <td>6.808746e+07</td>\n",
       "      <td>4.365700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>Xinjiang</td>\n",
       "      <td>23011800.0</td>\n",
       "      <td>9.592336e+07</td>\n",
       "      <td>4.168442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>云南省</td>\n",
       "      <td>Yunnan</td>\n",
       "      <td>48039800.0</td>\n",
       "      <td>2.060811e+08</td>\n",
       "      <td>4.289799</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2019-01-12</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>57347400.0</td>\n",
       "      <td>2.607327e+08</td>\n",
       "      <td>4.546548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4538</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>安徽省</td>\n",
       "      <td>Anhui</td>\n",
       "      <td>63233400.0</td>\n",
       "      <td>3.253027e+08</td>\n",
       "      <td>5.144476</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4533</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>北京市</td>\n",
       "      <td>Beijing</td>\n",
       "      <td>21542000.0</td>\n",
       "      <td>7.964508e+07</td>\n",
       "      <td>3.697200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4556</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>重庆市</td>\n",
       "      <td>Chongqing</td>\n",
       "      <td>31017900.0</td>\n",
       "      <td>1.325953e+08</td>\n",
       "      <td>4.274800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4553</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>福建省</td>\n",
       "      <td>Fujian</td>\n",
       "      <td>39410000.0</td>\n",
       "      <td>1.729166e+08</td>\n",
       "      <td>4.387634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4552</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>甘肃省</td>\n",
       "      <td>Gansu</td>\n",
       "      <td>26283200.0</td>\n",
       "      <td>1.133082e+08</td>\n",
       "      <td>4.311052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4541</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>广东省</td>\n",
       "      <td>Guangdong</td>\n",
       "      <td>112520300.0</td>\n",
       "      <td>4.556311e+08</td>\n",
       "      <td>4.049323</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4542</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>广西壮族自治区</td>\n",
       "      <td>Guangxi</td>\n",
       "      <td>48849600.0</td>\n",
       "      <td>2.243222e+08</td>\n",
       "      <td>4.592100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4554</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>贵州省</td>\n",
       "      <td>Guizhou</td>\n",
       "      <td>35790100.0</td>\n",
       "      <td>1.738335e+08</td>\n",
       "      <td>4.857028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4549</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>海南省</td>\n",
       "      <td>Hainan</td>\n",
       "      <td>3942000.0</td>\n",
       "      <td>1.707050e+07</td>\n",
       "      <td>4.330415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4546</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>河北省</td>\n",
       "      <td>Hebei</td>\n",
       "      <td>73910900.0</td>\n",
       "      <td>3.164876e+08</td>\n",
       "      <td>4.282015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4559</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>黑龙江省</td>\n",
       "      <td>Heilongjiang</td>\n",
       "      <td>35958300.0</td>\n",
       "      <td>1.313505e+08</td>\n",
       "      <td>3.652856</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4547</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>河南省</td>\n",
       "      <td>Henan</td>\n",
       "      <td>95383900.0</td>\n",
       "      <td>4.421247e+08</td>\n",
       "      <td>4.635213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4550</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>湖北省</td>\n",
       "      <td>Hubei</td>\n",
       "      <td>58458500.0</td>\n",
       "      <td>1.985759e+08</td>\n",
       "      <td>3.396869</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4551</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>湖南省</td>\n",
       "      <td>Hunan</td>\n",
       "      <td>68988200.0</td>\n",
       "      <td>3.100372e+08</td>\n",
       "      <td>4.494062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4532</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>内蒙古自治区</td>\n",
       "      <td>Inner Mongolia</td>\n",
       "      <td>25287000.0</td>\n",
       "      <td>1.267918e+08</td>\n",
       "      <td>5.014111</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4544</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>江苏省</td>\n",
       "      <td>Jiangsu</td>\n",
       "      <td>80507400.0</td>\n",
       "      <td>4.378573e+08</td>\n",
       "      <td>5.438722</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4545</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>江西省</td>\n",
       "      <td>Jiangxi</td>\n",
       "      <td>46196900.0</td>\n",
       "      <td>2.115044e+08</td>\n",
       "      <td>4.578325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4534</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>吉林省</td>\n",
       "      <td>Jilin</td>\n",
       "      <td>26156900.0</td>\n",
       "      <td>1.246441e+08</td>\n",
       "      <td>4.765247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4555</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>辽宁省</td>\n",
       "      <td>Liaoning</td>\n",
       "      <td>43955300.0</td>\n",
       "      <td>2.202319e+08</td>\n",
       "      <td>5.010361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4537</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>宁夏回族自治区</td>\n",
       "      <td>Ningxia</td>\n",
       "      <td>6817700.0</td>\n",
       "      <td>3.292324e+07</td>\n",
       "      <td>4.829083</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4558</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>青海省</td>\n",
       "      <td>Qinghai</td>\n",
       "      <td>5985800.0</td>\n",
       "      <td>2.604144e+07</td>\n",
       "      <td>4.350536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4557</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>陕西省</td>\n",
       "      <td>Shaanxi</td>\n",
       "      <td>38065700.0</td>\n",
       "      <td>1.713380e+08</td>\n",
       "      <td>4.501112</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4539</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>山东省</td>\n",
       "      <td>Shandong</td>\n",
       "      <td>99083400.0</td>\n",
       "      <td>5.013959e+08</td>\n",
       "      <td>5.060342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4530</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>上海市</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>24237800.0</td>\n",
       "      <td>1.330195e+08</td>\n",
       "      <td>5.488100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4540</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>山西省</td>\n",
       "      <td>Shanxi</td>\n",
       "      <td>37183300.0</td>\n",
       "      <td>1.670153e+08</td>\n",
       "      <td>4.491675</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4535</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>四川省</td>\n",
       "      <td>Sichuan</td>\n",
       "      <td>83398000.0</td>\n",
       "      <td>3.693623e+08</td>\n",
       "      <td>4.428911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4536</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>天津市</td>\n",
       "      <td>Tianjin</td>\n",
       "      <td>15596000.0</td>\n",
       "      <td>6.970944e+07</td>\n",
       "      <td>4.469700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4543</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>新疆维吾尔自治区</td>\n",
       "      <td>Xinjiang</td>\n",
       "      <td>23011800.0</td>\n",
       "      <td>1.063465e+08</td>\n",
       "      <td>4.621388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4531</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>云南省</td>\n",
       "      <td>Yunnan</td>\n",
       "      <td>48039800.0</td>\n",
       "      <td>2.352895e+08</td>\n",
       "      <td>4.897804</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4548</th>\n",
       "      <td>2020-03-16</td>\n",
       "      <td>浙江省</td>\n",
       "      <td>Zhejiang</td>\n",
       "      <td>57347400.0</td>\n",
       "      <td>2.998626e+08</td>\n",
       "      <td>5.228879</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4560 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     update_date province_name province_name_en   population         value  \\\n",
       "8     2019-01-12           安徽省            Anhui   63233400.0  2.907005e+08   \n",
       "3     2019-01-12           北京市          Beijing   21542000.0  8.371006e+07   \n",
       "26    2019-01-12           重庆市        Chongqing   31017900.0  1.236808e+08   \n",
       "23    2019-01-12           福建省           Fujian   39410000.0  1.531519e+08   \n",
       "22    2019-01-12           甘肃省            Gansu   26283200.0  1.045462e+08   \n",
       "11    2019-01-12           广东省        Guangdong  112520300.0  4.419054e+08   \n",
       "12    2019-01-12       广西壮族自治区          Guangxi   48849600.0  2.130164e+08   \n",
       "24    2019-01-12           贵州省          Guizhou   35790100.0  1.458346e+08   \n",
       "19    2019-01-12           海南省           Hainan    3942000.0  1.718801e+07   \n",
       "16    2019-01-12           河北省            Hebei   73910900.0  3.221683e+08   \n",
       "29    2019-01-12          黑龙江省     Heilongjiang   35958300.0  1.516191e+08   \n",
       "17    2019-01-12           河南省            Henan   95383900.0  4.365894e+08   \n",
       "20    2019-01-12           湖北省            Hubei   58458500.0  2.319045e+08   \n",
       "21    2019-01-12           湖南省            Hunan   68988200.0  2.879820e+08   \n",
       "2     2019-01-12        内蒙古自治区   Inner Mongolia   25287000.0  1.250565e+08   \n",
       "14    2019-01-12           江苏省          Jiangsu   80507400.0  3.886402e+08   \n",
       "15    2019-01-12           江西省          Jiangxi   46196900.0  2.002228e+08   \n",
       "4     2019-01-12           吉林省            Jilin   26156900.0  1.131208e+08   \n",
       "25    2019-01-12           辽宁省         Liaoning   43955300.0  1.940003e+08   \n",
       "7     2019-01-12       宁夏回族自治区          Ningxia    6817700.0  3.286388e+07   \n",
       "28    2019-01-12           青海省          Qinghai    5985800.0  2.333910e+07   \n",
       "27    2019-01-12           陕西省          Shaanxi   38065700.0  1.530453e+08   \n",
       "9     2019-01-12           山东省         Shandong   99083400.0  4.561063e+08   \n",
       "0     2019-01-12           上海市         Shanghai   24237800.0  1.028604e+08   \n",
       "10    2019-01-12           山西省           Shanxi   37183300.0  1.642341e+08   \n",
       "5     2019-01-12           四川省          Sichuan   83398000.0  3.390837e+08   \n",
       "6     2019-01-12           天津市          Tianjin   15596000.0  6.808746e+07   \n",
       "13    2019-01-12      新疆维吾尔自治区         Xinjiang   23011800.0  9.592336e+07   \n",
       "1     2019-01-12           云南省           Yunnan   48039800.0  2.060811e+08   \n",
       "18    2019-01-12           浙江省         Zhejiang   57347400.0  2.607327e+08   \n",
       "...          ...           ...              ...          ...           ...   \n",
       "4538  2020-03-16           安徽省            Anhui   63233400.0  3.253027e+08   \n",
       "4533  2020-03-16           北京市          Beijing   21542000.0  7.964508e+07   \n",
       "4556  2020-03-16           重庆市        Chongqing   31017900.0  1.325953e+08   \n",
       "4553  2020-03-16           福建省           Fujian   39410000.0  1.729166e+08   \n",
       "4552  2020-03-16           甘肃省            Gansu   26283200.0  1.133082e+08   \n",
       "4541  2020-03-16           广东省        Guangdong  112520300.0  4.556311e+08   \n",
       "4542  2020-03-16       广西壮族自治区          Guangxi   48849600.0  2.243222e+08   \n",
       "4554  2020-03-16           贵州省          Guizhou   35790100.0  1.738335e+08   \n",
       "4549  2020-03-16           海南省           Hainan    3942000.0  1.707050e+07   \n",
       "4546  2020-03-16           河北省            Hebei   73910900.0  3.164876e+08   \n",
       "4559  2020-03-16          黑龙江省     Heilongjiang   35958300.0  1.313505e+08   \n",
       "4547  2020-03-16           河南省            Henan   95383900.0  4.421247e+08   \n",
       "4550  2020-03-16           湖北省            Hubei   58458500.0  1.985759e+08   \n",
       "4551  2020-03-16           湖南省            Hunan   68988200.0  3.100372e+08   \n",
       "4532  2020-03-16        内蒙古自治区   Inner Mongolia   25287000.0  1.267918e+08   \n",
       "4544  2020-03-16           江苏省          Jiangsu   80507400.0  4.378573e+08   \n",
       "4545  2020-03-16           江西省          Jiangxi   46196900.0  2.115044e+08   \n",
       "4534  2020-03-16           吉林省            Jilin   26156900.0  1.246441e+08   \n",
       "4555  2020-03-16           辽宁省         Liaoning   43955300.0  2.202319e+08   \n",
       "4537  2020-03-16       宁夏回族自治区          Ningxia    6817700.0  3.292324e+07   \n",
       "4558  2020-03-16           青海省          Qinghai    5985800.0  2.604144e+07   \n",
       "4557  2020-03-16           陕西省          Shaanxi   38065700.0  1.713380e+08   \n",
       "4539  2020-03-16           山东省         Shandong   99083400.0  5.013959e+08   \n",
       "4530  2020-03-16           上海市         Shanghai   24237800.0  1.330195e+08   \n",
       "4540  2020-03-16           山西省           Shanxi   37183300.0  1.670153e+08   \n",
       "4535  2020-03-16           四川省          Sichuan   83398000.0  3.693623e+08   \n",
       "4536  2020-03-16           天津市          Tianjin   15596000.0  6.970944e+07   \n",
       "4543  2020-03-16      新疆维吾尔自治区         Xinjiang   23011800.0  1.063465e+08   \n",
       "4531  2020-03-16           云南省           Yunnan   48039800.0  2.352895e+08   \n",
       "4548  2020-03-16           浙江省         Zhejiang   57347400.0  2.998626e+08   \n",
       "\n",
       "       n_value  \n",
       "8     4.597262  \n",
       "3     3.885900  \n",
       "26    3.987400  \n",
       "23    3.886118  \n",
       "22    3.977683  \n",
       "11    3.927339  \n",
       "12    4.360659  \n",
       "24    4.074720  \n",
       "19    4.360226  \n",
       "16    4.358874  \n",
       "29    4.216526  \n",
       "17    4.577181  \n",
       "20    3.966995  \n",
       "21    4.174366  \n",
       "2     4.945486  \n",
       "14    4.827385  \n",
       "15    4.334118  \n",
       "4     4.324702  \n",
       "25    4.413582  \n",
       "7     4.820376  \n",
       "28    3.899077  \n",
       "27    4.020557  \n",
       "9     4.603257  \n",
       "0     4.243800  \n",
       "10    4.416878  \n",
       "5     4.065850  \n",
       "6     4.365700  \n",
       "13    4.168442  \n",
       "1     4.289799  \n",
       "18    4.546548  \n",
       "...        ...  \n",
       "4538  5.144476  \n",
       "4533  3.697200  \n",
       "4556  4.274800  \n",
       "4553  4.387634  \n",
       "4552  4.311052  \n",
       "4541  4.049323  \n",
       "4542  4.592100  \n",
       "4554  4.857028  \n",
       "4549  4.330415  \n",
       "4546  4.282015  \n",
       "4559  3.652856  \n",
       "4547  4.635213  \n",
       "4550  3.396869  \n",
       "4551  4.494062  \n",
       "4532  5.014111  \n",
       "4544  5.438722  \n",
       "4545  4.578325  \n",
       "4534  4.765247  \n",
       "4555  5.010361  \n",
       "4537  4.829083  \n",
       "4558  4.350536  \n",
       "4557  4.501112  \n",
       "4539  5.060342  \n",
       "4530  5.488100  \n",
       "4540  4.491675  \n",
       "4535  4.428911  \n",
       "4536  4.469700  \n",
       "4543  4.621388  \n",
       "4531  4.897804  \n",
       "4548  5.228879  \n",
       "\n",
       "[4560 rows x 6 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_if"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_if_nation = data_if.groupby(['update_date'])[\"population\", \"value\"].apply(lambda x : x.sum()).reset_index()\n",
    "data_if_nation['n_value'] = data_if_nation.apply (lambda row: row.value/row.population, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_if_city.to_csv(r'./data/data_bdqx_if_city.csv', index = False)\n",
    "data_if.to_csv(r'./data/data_bdqx_if_province.csv', index = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plot the internal flow index: national, provincial (Hubei), and city level (Wuhan)\n",
    "def figure_if(df, subject, fs = 12):\n",
    "    df = df[df['update_date'] >= datetime.date(int(2020),int(1),int(1))]\n",
    "    df = df.reset_index(drop = True)\n",
    "    fig = plt.figure(figsize = (12, 5))\n",
    "    ax = plt.subplot(111)\n",
    "    sns.set_style('whitegrid')\n",
    "    timespan = (max(df.update_date) - min(df.update_date)).days + 1\n",
    "    T = (datetime.date(int(2020),int(1),int(21)) - min(df.update_date)).days + 1\n",
    "    TT = (datetime.date(int(2020),int(1),int(31)) - min(df.update_date)).days + 1\n",
    "    TTT = (datetime.date(int(2020),int(2),int(21)) - min(df.update_date)).days + 1\n",
    "    first_list = [True]*T + [False]*(timespan - T)\n",
    "    second_list = [False]*TT + [True]*(TTT - TT) + [False]*(timespan - TTT)\n",
    "    first_mean = np.mean(np.multiply(df.n_value.tolist(), first_list))*timespan/T\n",
    "    second_mean = np.mean(np.multiply(df.n_value.tolist(), second_list))*timespan/(TTT - TT)\n",
    "    y_min, y_max = np.round(min(df.n_value), 1)*0.95, np.round(max(df.n_value), 1)*1.05\n",
    "    first_index = [first_mean]*timespan\n",
    "    second_index = [second_mean]*timespan\n",
    "    palette = plt.get_cmap('bone_r')\n",
    "    ax.scatter(df['update_date'], df['n_value'],\n",
    "               marker = 'o', \n",
    "               color = [rgb2hex(palette(temp/5)) for temp in df['n_value'].tolist()],\n",
    "               label = None)\n",
    "    ax.plot(df['update_date'], df['n_value'], linewidth = 2,\n",
    "            color = palette(0.5), label = None)\n",
    "    ax.plot(list(compress(df['update_date'], first_list)), list(compress(first_index, first_list)), \n",
    "            linewidth = 2, color = palette(first_mean/7), label = 'average plateau')\n",
    "    ax.plot(list(compress(df['update_date'], second_list)), list(compress(second_index, second_list)), \n",
    "            linewidth = 2, color = palette(second_mean/7), label = 'lockdown plateau')\n",
    "    ax.set_xlim(min(df.update_date), max(df.update_date))\n",
    "    ax.xaxis.set_major_locator(mdates.WeekdayLocator())\n",
    "    ax.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d'))\n",
    "    # these are matplotlib.patch.Patch properties\n",
    "    props_first = dict(boxstyle = 'round', facecolor = palette(first_mean/10), alpha = 0.5)\n",
    "    props_second = dict(boxstyle = 'round', facecolor = palette(second_mean/10), alpha = 0.5)\n",
    "    ax.set_ylim(np.round(min(df.n_value), 1) - 0.2, np.round(max(df.n_value), 1) + 0.2)\n",
    "    shift = 0.25\n",
    "    \n",
    "    # place two text boxes\n",
    "    ax.text(0/timespan + 0.03, (first_mean - y_min)/(y_max - y_min) - shift,\n",
    "            'average plateau: ' + str(round(first_mean, 4)), \n",
    "            transform = ax.transAxes, fontsize = fs,\n",
    "            verticalalignment = 'center', bbox=props_first)\n",
    "    ax.text(TT/timespan + 0.03, (second_mean - y_min)/(y_max - y_min) + shift,  # - 0.25, - 0.1\n",
    "            'average plateau: ' + str(round(second_mean, 4)), \n",
    "            transform = ax.transAxes, fontsize = fs,\n",
    "            verticalalignment = 'center', bbox=props_second)\n",
    "    ax.set_title(subject + ': internal flow (' + str(round(second_mean/first_mean*100, 2)) + '% contact rate)', fontsize = fs + 2) \n",
    "    ax.set_xlabel('Date', fontsize = fs)\n",
    "    if subject == 'Wuhan':\n",
    "        ax.set_ylabel('Ratio', fontsize = fs)\n",
    "    else:\n",
    "        ax.set_ylabel('Normalized ratio', fontsize = fs)\n",
    "    ax.tick_params(axis = 'both', which = 'major', labelsize = fs - 2)\n",
    "    ax.tick_params(axis = 'both', which = 'minor', labelsize = fs - 2)\n",
    "    fig.savefig(_Figure_PATH_ + subject + '_IF.png', dpi = 400)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure_if(data_if_nation, 'China', 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_if_Hubei = data_if[data_if['province_name_en'] == 'Hubei']\n",
    "data_if_Hubei = data_if_Hubei.reset_index(drop = True)\n",
    "figure_if(data_if_Hubei, 'Hubei', 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_if_Wuhan = data_if_city[data_if_city['city_name'] == '武汉市']\n",
    "data_if_Wuhan = data_if_Wuhan.reset_index(drop = True)\n",
    "data_if_Wuhan['n_value'] = data_if_Wuhan['ratio']\n",
    "figure_if(data_if_Wuhan, 'Wuhan', 14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "date_initial = datetime.date(int(2020),int(1),int(7))\n",
    "date_tr = datetime.date(int(2020),int(3),int(10))\n",
    "data_if_province = data_if[(data_if.update_date >= date_initial) & (data_if.update_date <= date_tr)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Plot the internal flow index: provincial (every province)\n",
    "def figure_IF(df, fsize= (10, 6), fs = 16, title = 'City migration'):\n",
    "    fig, ax = plt.subplots(figsize = fsize)\n",
    "    sns.set_style(\"whitegrid\")\n",
    "    palette = plt.get_cmap('bone')\n",
    "    i = 0\n",
    "    for key, grp in df.groupby(['province_name_en']):\n",
    "        if key!='Hubei':\n",
    "            ax = grp.plot(ax = ax, x='update_date', y='n_value', style = '-', color = palette(i/50 + 0.2), label = key)\n",
    "        else:\n",
    "            ax = grp.plot(ax = ax, x='update_date', y='n_value', style = '-', marker = 'o', color = palette(i/50 + 0.2), label = key)\n",
    "        i += 1\n",
    "    plt.legend(loc='upper center', ncol = 6, fancybox = True, fontsize = fs - 5)\n",
    "    ax.set_xlabel(\"Date\", fontsize = fs - 2)\n",
    "    ax.set_ylabel(\"Normalized ratio\", fontsize = fs - 2)\n",
    "    ax.set_title('China: provincial internal flow', fontsize = fs)\n",
    "    ax.set_xlim(min(df.update_date), max(df.update_date))\n",
    "    ax.xaxis.set_major_locator(mdates.WeekdayLocator())\n",
    "    ax.xaxis.set_major_formatter(mdates.DateFormatter('%m-%d'))\n",
    "    fig.savefig(_Figure_PATH_ + 'China_Province_IF.png', dpi = 400)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure_IF(df = data_if_province, fsize= (12, 6), fs = 16, title = 'City migration')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "#data_if_single = data_if_city[data_if_city.update_date == datetime.date(int(2020),int(1),int(31))]\n",
    "#data_if_single = data_if_single[data_if_single.province_name == '湖北省']\n",
    "#data_if_single.sort_values(by = 'population')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
